Download Chapter 1 - Research Explorer

UvA-DARE (Digital Academic Repository)
Isovaleric acidemia: an integrated approach toward predictive laboratory medicine
Dercksen, M.
Link to publication
Citation for published version (APA):
Dercksen, M. (2014). Isovaleric acidemia: an integrated approach toward predictive laboratory medicine
General rights
It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s),
other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
Disclaimer/Complaints regulations
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating
your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask
the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam,
The Netherlands. You will be contacted as soon as possible.
UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl)
Download date: 14 Jun 2017
Chapter 1
General introduction and outline of thesis
1
Chapter 1
1
Preface
Organic acidemias are an important group of inborn errors of metabolism (IEMs), which
mainly involve defects in the catabolism and related intermediary pathways of
carbohydrates, amino acids and fatty acids. Some organic acidemias can be treated
with a relatively high success rate, but this may depend on rapid diagnosis and early
treatment interventions. Treatment is in general aimed to reduce metabolic
decompensation as well as to prevent neurological damage and developmental delay.
The phenotypical presentation of the organic acidemias is broad.
Isovaleric acidemia (IVA), which is the result of the defective isovaleryl-CoA
dehydrogenase (IVD) in the catabolism of leucine, a branched chain amino acid
(BCAA), was one of the first organic acidemias to be described, almost 50 years ago by
Tanaka et al. (1966). Subsequently, Budd et al. (1967) clarified the primary clinical
manifestations of the disease. A large number of case studies have progressively
emphasized the clinical heterogeneity of IVA (reviewed by Ensenauer et al., 2004;
Vockley and Ensenauer, 2006). These reviews indicate that the original notion of a one
genotype, one phenotype relationship is probably the exception rather than the rule,
because the disorder is accompanied by neurological aberrations in varying degrees
(Budd et al., 1967; Grünert et al., 2012). The clinical variability, even in patients with the
same genetic background, as well as novel diagnostic biochemical tools and expanding
treatment possibilities for isovaleric acidemia, served as main motivation for this study.
A timely diagnosis of IVA, through newborn screening (NBS) programs around the world
has improved the clinical outcome of most patients by the early implementation of
treatment. The development of mass spectrometry for NBS has led to the identification
of IEM patients with an unexpectedly wide clinical presentation (Ensenauer et al., 2004;
Dionisi-Vici et al., 2006). Recent investigations of IVA patients in Korea, Taiwan and
Thailand have further emphasized the diversity of genotype-phenotype relationships in
different populations and even within families (Lee et al., 2007; Lin et al., 2007;
Vatanavicharn et al., 2011). IVA is periodically diagnosed in the Caucasian South
African population (although its prevalence is still unknown). The molecular and
biochemical characteristics, however, have been poorly documented thus far.
Consequently, the characterization of IVA in the South African population was one of
the main aims of this study. Nutritional and pathological aspects were also subjects of
investigation.
A crucial additional factor in the conduct of the research reported in this thesis is the
advent of metabolomics, which is a highly sensitive, data-driven technology responsible
for novel multidisciplinary approaches (as will be described in section 6 of this chapter)
that permit the interpretation of pathophysiological aspects of disease. The metabolomic
approach has also irrefutably led to the first proof-of-concept studies in IEMs, namely
2
General introduction and outline of thesis
defects in the metabolism of propionate (Wikoff et al., 2007) and respiratory chain
disorders (Smuts et al., 2012). The study of the metabolome and its changes in
response to different physiological and genetic processes already shows promise in the
identification of the mechanism of disease and of underlying problems associated with
such disorders, for example pathological effects and nutritional deficiencies. A
metabolomic analysis may ultimately be able to determine the choice of therapy,
recognize susceptible patients and predict possible toxic effects of treatment (McCabe,
2010; Mamas et al., 2011). An exciting further spin-off may be the follow-up
investigations of the disease which will ultimately lead towards predictive laboratory
medicine. The recognition of the unique potential of metabolomics in the investigation of
IEMs therefore became one of the aims of this investigation, as will be elaborated on in
this chapter.
The following sections address topics that have a close bearing on the study reported in
this thesis. The initial discussion will outline the metabolism of branched chain amino
acids (BCAA) in general, and present an overview of IVA.
2
Metabolism of branched chain amino acids
The branched chain amino acids (BCAA) leucine, isoleucine and valine, are essential
biomolecules which play a vital role as building blocks in protein synthesis. These
neutral aliphatic amino acids, containing methyl-branched side-chains are present in
protein-containing food. BCAAs are metabolized predominantly in the skeletal muscle
and the liver (>70%). Between 8 – 30% of the oxidation of BCAAs may also take place
in kidney -, brain -, heart -, pancreatic -, intestinal - and adipose tissue (Suryawan et al.,
1998). The degradation of these compounds results in the formation of important
metabolites, which are vital in biochemical processes (e.g. in the biosynthesis of lipids),
as well as in energy production (via the Krebs cycle and ketone body production).
The degradation of the BCAAs starts with their initial transportation into the cell via a
distinct L-amino acid-specific transporter, most likely Na+-independent (Shotwell and
Oxender, 1983). The initial transamination step, identical for all three BCAAs, takes
place in the cytosol via branched chain aminotransferase. Alternatively, BCAAs can also
be transported into the mitochondria (with a neutral amino acid carrier protein) and
converted into the corresponding branched chain keto acids (BCKAs) via mitochondrial
branched chain aminotransferase. Both aminotransferases are pyridoxal phosphatedependent and simultaneous amination of 2-ketoglutarate takes place to form
glutamate. The aminotransferase step for leucine, isoleucine and valine is not
individually regulated; however, the catabolism of each of the BCAAs is highly regulated
by both allosteric and covalent mechanisms (recently reviewed by Chuang et al., 2012).
3
Chapter 1
The branched chain keto acids will have to cross the mitochondrial membrane through
the action of a keto acid transporter. Once inside the mitochondria, all three branched
chain keto acids are oxidatively decarboxylated via the branched chain keto acid
dehydrogenase (BCKAD) complex to form branched chain acyl-CoAs. BCKAD is a
multi-enzyme complex consisting of three subunits, namely: E1, a thiamine
pyrophosphate-dependent decarboxylase; E2, a lipoamide acyltransferase; and E3, a
FAD- and NAD-containing dihydrolipoyl dehydrogenase (Chuang et al., 2012). The
sequential metabolic steps for each branched chain acyl-CoA differ and are illustrated in
Fig. 1. In view of the focus in this thesis on isovaleryl-CoA dehydrogenase deficiency,
this overview will deal mainly with the leucine degradation pathway (Fig. 1).
Leucine is transaminated to 2-oxoisocaproic acid, which is subsequently converted to
isovaleryl-CoA. Isovaleryl-CoA is resistant to β-oxidation, because of the methyl-group
at the carbon-3 position and instead undergoes a carboxylation step catalyzed by biotindependent 3-methylcrotonyl-CoA carboxylase (3-MCC) to form 3-methylglutaconyl-CoA.
The latter is hydrated by 3-methylglutaconyl-CoA hydratase to form 3-methyl-3hydroxyglutaryl-CoA, which is followed by a lyase step [3-hydroxy-3-methylglutaryl-CoA
lyase (HMG-CoA lyase)], resulting in the formation of acetyl-CoA and acetoacetate. The
ketone body acetoacetate can readily be converted into the other ketone body D-3hydroxybutyric acid. Both ketone bodies are produced in the liver and can be
transported to peripheral tissues as an alternative energy source. The catabolism of
leucine and several defects in this pathway have been reassessed recently by Vockley
et al. (2012). Isovaleryl-CoA dehydrogenase deficiency will be discussed in detail in this
chapter. Some aspects of the BCAA metabolism do not fall within the scope of these
investigations, but are mentioned in relevant sections of this thesis.
4
General introduction and outline of thesis
Fig 1: The catabolic pathways of BCAAs with special focus on the degradation of leucine
(highlighted in blue) (Vockley et al., 2012). Numbers indicate the enzymatic steps within the
catabolic pathways: 1) branched chain aminotransferase; 2) branched chain keto acid
dehydrogenase complex; 3) isobutyryl-CoA dehydrogenase or Acad 9; 4) enoyl-CoA
hydratase/crotonase; 5) 3-hydroxyisobutyryl-CoA hydrolase; 6) 3-hydroxyisobutyric acid
dehydrogenase; 7) methylmalonic semialdehyde dehydrogenase; 8) propionyl-CoA carboxylase; 9)
methylmalonyl-CoA racemase; 10) methylmalonyl-CoA mutase; 11) short/branched chain acyl-CoA
dehydrogenase; 12) enoyl-CoA hydratase/crotonase; 13) 2-methyl-3-hydroxybutyryl-CoA
dehydrogenase; 14) β-ketothiolase; 15) isovaleryl-CoA dehydrogenase; 16) 3-methylcrotonyl-CoA
carboxylase; 17) 3-methylglutaconyl CoA hydratase; 18) 3-hydroxy-3-methylglutaryl-CoA lyase.
5
Chapter 1
2.1 The disorders of leucine degradation
Defects in the leucine pathway give rise to amino acidopathies and/or organic acidemias
with
multisystemic
pathophysiological
consequences,
including
neurological
dysfunction. Disorders of the leucine metabolism include the BCKADH complex
deficiency or Maple Syrup Urine Disease (which affects all three branched chain amino
acids), isovaleryl-CoA dehydrogenase deficiency, 3-methylcrotonyl-CoA carboxylase
deficiency,
3-methylglutaconyl-CoA
hydratase
deficiency
and
3-hydroxy-3-
methylglutaryl-CoA lyase deficiency.
Co-factors derived from several vitamins such as riboflavin, biotin, thiamine and
pyridoxine are vital catalysts in the enzymatic steps of this pathway. Any deficiency in
these cofactors may have an impact on several parts of the BCAA catabolic pathways.
Good examples of such deficiencies are riboflavin-transporter deficiency, which affects
the degradation of short-chain and short/branched chain acyl-CoAs, including isovalerylCoA and 2-methylbutyryl-CoA (Bosch et al., 2011) and the biotin-related disorder due to
biotinidase deficiency (Bartlett et al., 1980) which affects 3-methylcrotonyl-CoA
carboxylase. Many of the primary enzyme and/or cofactor-related disorders in the BCAA
catabolic pathways are known to be partially or successfully treatable via timely
diagnosis, early dietary intervention and the supplementation of relevant cofactors. (see
reviews by Ogier de Baulny et al., 2012; Vockley et al., 2012). HMG-CoA lyase
deficiency, a defect of the terminal leucine catabolic pathway, is associated with a
complete inability to form ketones; correspondingly, affected patients are at risk of
developing non-ketotic hypoglycemia which is often fatal. Avoidance of fasting is the
only therapeutic option. Isovaleric acidemia (IVA), a defect located in the proximal part
of the leucine catabolic pathway, is a good example of a treatable organic acidemia
which requires dietary intervention as well as detoxifying agents.
2.2 Isovaleric acidemia
Isovaleric acidemia (IVA), an autosomal recessive disorder caused by isovaleryl-CoA
dehydrogenase (IVD) deficiency (E.C.1.2.99.10), is a well-defined organic acidemia
(Tanaka et al., 1966; Budd et al., 1967). This disorder has been described in
consanguineous and non-consanguineous families, as well as in various ethnic groups.
The incidence of IVA has been reported to be 1:62 500 in Germany, 1:250 000 in the
USA and 1:365 000 in Taiwan (Ensenauer et al., 2004; Lin et al., 2007). These
differences may possibly be attributed to founder effects in some populations. Currently,
over 40 mutations in the IVD gene have been described. The nucleotide and amino acid
variations, referred to in this thesis, are described in accordance with the Human Gene
Mutation Database (HGMD) nomenclature, and have recently been renumbered and
6
General introduction and outline of thesis
based on cDNA sequence in accordance with the GenBank entries NM_002225.3 and
NP_002216.2 (http://www.hgmd.org; Hertecant et al., 2012). The following sections will
initially discuss the biochemical abnormalities of IVA. These anomalies in the catabolism
of leucine result in a clinical spectrum of IVA and will be discussed at the end of section
2.2.
2.2.1
Abnormal metabolites and biochemical mechanisms
Isovaleric acid (Tanaka et al., 1966), N-isovalerylglycine (Tanaka and Isselbacher,
1967) 3-hydoxyisovaleric acid (3-HIVA) (Tanaka et al., 1968) and isovalerylcarnitine
(Roe et al., 1984) have been identified as the primary metabolic indicators of IVA and
are still reliable diagnostic markers for the disease with exception of free isovaleric acid
which escapes most of the currently applied chromatographic analyses. The
accumulating substrate isovaleryl-CoA and the subsequent formation of metabolites
through secondary metabolic pathways result in various biochemical changes which
may have a serious clinical impact.
Isovaleryl-CoA and subsequently isovaleric acid may increase several hundred fold
during a metabolic crisis (Vockley et al., 2012). Both isovaleryl-CoA and isovaleric acid
have been implicated in the inhibition or dysfunction of various enzymes and in
biochemical mechanisms which consequently cause neurotoxicity and related clinical
abnormalities. Early investigations have shown isovaleryl-CoA to inhibit the pyruvate
dehydrogenase complex (in pig liver), resulting in elevated lactic acid levels during a
metabolic crisis (Gregersen, 1981). The influence of isovaleryl-CoA on pyruvate
carboxylase has been examined in several bacterial as well as mammalian species, but
no effect on the activity of this enzyme was observed (Scrutton, 1974; Zeczycki et al.,
2010).
Enzymes of the Krebs cycle are also influenced to some degree. The inhibition of
succinyl-CoA ligase by isovaleryl-CoA in rat liver has been reported (Bergen et al.,
1982). This is a serious potential side effect of isovaleryl-CoA, as it is known today that
a complete absence of succinyl-CoA ligase results in mitochondrial DNA-depletion
(Carrozzo et al., 2007). Furthermore, some studies suggest that the accumulation of
acyl-CoAs (of various chain lengths) may affect the function of the 2-ketoglutarate
dehydrogenase complex, isocitrate dehydrogenase, malate dehydrogenase and citrate
synthase to varying degrees (Stumpf et al., 1985; Lai et al., 1991; Lai et al., 1994).
However, the inhibition of these enzymes by isovaleryl-CoA has not been specifically
confirmed in these investigations. Isovaleryl-CoA can further act as an inhibitor of Nacetylglutamate synthase, the first step in the urea cycle, which thereby contributes to
secondary hyperammonemia observed in isovaleric acidemia (Coude et al., 1979;
7
Chapter 1
Lehnert, 1981b). A report by Lai et al. (1991) showed that an elevated ammonia level,
which is present during a metabolic crisis, may amplify the inhibitory effect of acyl-CoAs
(of different chain lengths) on mitochondrial enzymes (as described above).
Isovaleric acid has been implicated in cerebral dysfunction in addition to the primary
disturbance of energy production in the mitochondria. It was found that the in vivo
administration of isovaleric acid inhibits Na+,K+-ATPase activity. The latter enzyme is
important in maintaining the basal membrane potential, which is vital for adequate
neurotransmission and consequently for energy production in the brain (Dahl, 1968; Lai
et al., 1991; Ribeiro et al., 2007). Furthermore, a report by Solano et al. (2008)
suggested that elevated levels of isovaleric acid and N-isovalerylglycine may be
involved in oxidative damage within the mitochondria and consequently be partially
responsible for the neuropathological features of IVA.
The involvement of N-
isovalerylglycine is somewhat controversial, because no supportive evidence of Nisovalerylglycine and its relation to neurotoxicity has been put forward yet. In brief, the
precise elucidation of the mechanism of neurotoxicity due to the accumulation of
isovaleryl-CoA and/or isovaleric acid (and potentially N-isovalerylglycine), is still strongly
debated.
Increased isovaleryl-CoA may also participate in acylation reactions, as well as (ω-1)hydroxylation and ω-oxidation reactions (Lehnert and Niederhoff, 1981; Lehnert, 1981b;
Truscott et al., 1981; Millington et al., 1987; Tanaka et al., 1988; Loots et al., 2005). Fig.
2 depicts the secondary transformation of the accumulating isovaleryl-CoA in IVA. The
formation of 3-hydroxyisovaleric acid has been attributed to several secondary
pathways namely (ω-1)-hydroxylation (Tanaka et al., 1968) and/or liver specific αketoisocaproate dioxygenase (Sabourin and Bieber, 1982; Van Kovering and Nissen,
1992). Recent findings of the inhibition of 3-methylcrotonyl-CoA carboxylase by
isovaleryl-CoA
may
subsequently
contribute
to
the
further
formation
of
3-
hydroxyisovaleric acid (3-HIVA) (Luís et al., 2012). The neurotoxicity of 3-HIVA is still
being questioned. Indeed, 3-HIVA has been suggested to have neurotoxic properties by
Duran et al. (1993). However, Ribeiro et al. (2007) and Van der Graaf et al. (2010)
found no correlation between the neurological features and the extent to which 3-HIVA
was elevated in these patients.
Due to the described aberrant effects in the mitochondria of IVA cells, we can only
assume that energy production is severely compromised and that mitochondrial
homeostasis is in disarray. The increased rate of fatty acid oxidation needed for energy
production as well as elevated 3-ketothiolase activity using isovaleryl-CoA and acetylCoA as substrates potentially lead to mitochondrial CoA depletion (Lehnert 1981a;
Vockley et al., 2012). The restricted availability of free CoA consequently limits the
8
General introduction and outline of thesis
function of the CoA-carnitine exchange mechanism, which further debilitates
mitochondrial functioning (Mitchell et al., 2008).
The accumulation of isovaleryl-CoA may further influence fatty acid synthesis. Similar
effects have been observed in the production of odd-numbered fatty acids from
propionyl-CoA in patients with propionic acidemia and methylmalonic acidemia (Lynen,
1961; Wendel et al., 1995). One short report indicated that isovaleryl-CoA, together with
malonyl-CoA, can act as substrates in the production of branched odd-chain fatty acids
but further investigation is needed to assess the influence on lipid biosynthesis (Malins
et al., 1972). Loots (2009) reported that methylsuccinic acid, a homologue of succinate
formed during ω-oxidation of isovaleryl-CoA, acts as a precursor substrate for the
production of methylated tricarboxylic acid cycle intermediates and therefore contributes
substantially to the disruption of energy production. Taken together, cellular
homeostasis may be disrupted due to several biochemical aberrations as a result of the
IVD deficiency.
9
Chapter 1
Fig 2: Schematic representation of important secondary metabolites formed via alternative
pathways in the case of an IVD deficiency. Numbers indicate related enzymes or processes: 1:
aminotransferase; 2: branched chain 2-keto dehydrogenase; 3: N-glycine acylase/acylation; 4: Nacetylglutamate synthase; 5: carnitine acetyl-CoA transferase; 6: thiolase; 7: 3-hydroxy-3methylglutaryl-CoA synthase; 8: 3-hydroxy-3-methylglutaryl-CoA lyase; 9: 3-hydoxybutyrate
dehydrogenase; 10: glucuronidation; 11: thio-esterification; 12: (ω-1)-hydroxylation and/or αketoisocaproate dioxygenase; 13: ω-oxidation; 14: succinate dehydrogenase. Abbreviations: R1: αaminobutyric acid, alanine, aspartic acid, asparagine, glycine, histidine, leucine, lysine,
phenylalanine, serine, threonine, tryptophan, tyrosine, or valine (Van Kovering and Nissen, 1992;
Loots et al., 2005; Vockley et al., 2012).
The debilitating effect of isovaleryl-CoA during primary decompensation is mostly
counteracted by the production of the metabolites indicated in Fig. 2. The body's natural
10
General introduction and outline of thesis
detoxification pathways which will effectively remove accumulating isovaleryl-CoA from
the mitochondria are maximally activated. Isovaleryl-CoA may be conjugated with
glycine via glycine-N-acylase to form N-isovalerylglycine, which is polar and watersoluble and can therefore be excreted via the kidneys (Krieger and Tanaka, 1976).
Acylation with other amino acids such as alanine, sarcosine and serine has also been
reported (Yudkoff et al., 1978; Lehnert, 1983; Loots et al., 2005). Further conjugation
with glucuronic acid (Dorland et al., 1983; Hine and Tanaka, 1984) and L-carnitine (Roe
et al., 1984) results in (partially) detoxified conjugates which are readily excreted in the
urine. Investigation of the biochemical profile of these patients has revealed free
carnitine depletion in plasma and urine, which suggested the formation of
isovalerylcarnitine (Stanley et al., 1983; Roe et al., 1984).
The decrease in plasma glycine level during an oral leucine loading test was reported by
Yudkoff et al. (1978), which suggested the enhanced production of N-isovalerylglycine.
However, the latter study did not clearly reveal depletion of glycine, such as in the case
of L-carnitine. Isovaleryl-CoA may further on enter the ketone body synthesis pathway
via 3-ketothiolase which then enters the HMG-CoA cycle (Lehnert, 1981a). The
subsequent formation of long-chain ketones, i.e. 3-hydroxyisoheptanoic acid and its
related keto acid, are probably useless as alternative energy sources in the peripheral
tissues. The detoxification of accumulating substrates and the therapeutic importance
through conjugation of isovaleryl-CoA will be discussed further in section 4 of this
chapter.
2.2.2
IVD enzyme characteristics
Human IVD is initially produced in the cytosol as a 45 kDa precursor molecule and
imported into the mitochondria, after which it is proteolytically cleaved to form a 43 kDa
monomer. The active 172 kDa homotetramer is assembled in the mitochondria and one
mole of the cofactor, flavin adenine dinucleotide (FAD), is added to each subunit (Ikeda
and Tanaka. 1983; Ikeda et al., 1984; Ikeda et al., 1987). FAD transfers electrons to the
electron transfer flavoprotein (ETF) during the IVD reaction. These electrons are further
transmitted to coenzyme Q in the respiratory chain via ETF dehydrogenase (McKean et
al., 1983, Tiffany et al., 1997). Isovaleryl-CoA has been identified as by far the best
substrate for IVD. Valeryl-CoA (46%), butyryl-CoA (21%) and hexanoyl-CoA (15%)
showed some affinity for recombinant human IVD compared to isovaleryl-CoA set to
100% activity. Other branched/short-chain CoAs such as 2-methylbutyryl-CoA and
isobutyryl-CoA showed virtually no activity with IVD (Ikeda and Tanaka, 1983; Mohsen
and Vockley, 1995).
11
Chapter 1
IVD is one of at least eight defined mammalian acyl-CoA dehydrogenases which have
been isolated from mitochondria, each with different substrate specificity. Four enzymes
– IVD, short/branched chain acyl-CoA dehydrogenase, isobutyryl-CoA dehydrogenase
and glutaryl-CoA dehydrogenase – are involved in amino acid catabolism. The other
four acyl-CoA dehydrogenase enzymes have straight-chain substrate specificities –
short- (SCAD), medium- (MCAD), long- (LCAD), and very long- (VLCAD) chain acylCoA dehydrogenase – and catalyze the first step of mitochondrial β-oxidation of fatty
acids with various chain lengths. In addition to their sequence similarities, all acyl-CoA
dehydrogenases exhibit similar biochemical properties and catalytic mechanisms
(Tiffany et al., 1997; Battaile et al., 2004). The IVD proteins from different species share
85–90% amino acid sequence identity (Mohsen et al., 1998)
IVD protein identification using Western blot technology, as well as enzymatic analysis
of IVD, have been well studied in the past, but not seen as necessary or as vital tools for
diagnostic purposes. This was because IVA was believed to be associated with a
distinct urine/plasma metabolite profile, namely grossly elevated N-isovalerylglycine and
isovalerylcarnitine
accompanied
by
3-hydroxyisovaleric
acid.
The
recent
acknowledgement of heterogeneity within IVA, however, warrants the investigation of
the IVD protein and its associated enzyme activity to conclusively identify and detail the
anomaly at the biochemical level. Mutations described early on by Mohsen et al. (1998),
associated with the "classical" presentation of IVD, in general, showed no expressed or
active IVD protein, exemplified by the case of p.L45P. This is in contrast to mild IVA,
which is associated with the amino acid change, p.A314V.
12
General introduction and outline of thesis
Fig 3: The three-dimensional molecular structure of IVD at 2.6 Å (MMDB: 49718 and 1IVH). The
IVD homotetramer is shown in 4 different colours. The substrate (isovaleryl-CoA) and cofactor
(FAD) are represented as "stick" components within the structure. [The image was generated using
the Cn3D program (Wang et al., 2000).]
Lee et al. (2007) observed a limited IVD protein signal and no residual IVD activity in
Korean patients with various mutations in the IVD gene. The IVD protein due to the
splice site mutation 153+1G > T showed the weakest signal on immunoblot analysis,
compared to missense mutations which were also identified in this Asian population.
The position of the mutation does not always explain the influence on the expression of
the IVD protein. Some amino acid changes are directly responsible for a change in the
binding pocket of substrates. As an example, p.Y403C affects the FAD binding to IVD
(Lin et al., 2007). Other amino acid substitutions are not in close proximity to the
substrate binding position, but may still be responsible for no or limited IVD expression
or activity, probably due to the instability of the protein or faulty protein folding (Mohsen
et al., 1998). Vockley and Ensenauer (2006) indicated that the activity of IVD could
partly explain the clinical phenotype, although in a few patients only. Furthermore, they
suggested that pharmaceutical "chaperones" may be used to optimize protein folding in
certain mutated enzymes (discussed in section 4 of this chapter).
13
Chapter 1
Several enzyme assays have been set up and tested with variable success. The original
methods involved the indirect measurement of IVD activity, which included the use of (1)
the DCPIP dye reduction assay with artificial electron acceptors (Rhead et al., 1981;
Okamura-Ikeda et al., 1985) or (2) the ETF fluorescence analysis, which was initially
described by Frerman and Goodman (1985) and modified by Mohsen and Vockley
(1995). These are still the methods of choice but have turned out to be inadequate in
several respects. The DCPIP dye reduction assay results in a relatively high assay
background and can only be performed in isolated mitochondria. The ETF fluorescence
assay has to be performed under strict anaerobic conditions, and the commercial
unavailability of ETF is a definite problem. The measurement of acyl-CoA
dehydrogenase activities (ACADs), including IVD, was recently reviewed and optimized
by Wanders et al. (2010). Direct measurement of the enzyme can be achieved through
the use of ferricenium hexafluorophosphate, which is commercially available as a
stable, albeit artificial electron acceptor and substitutes for ETF. The products of the
ACAD reaction can be identified by HPLC coupled to UV detection or by UPLC coupled
to tandem MS detection. This method has been chosen as the method of choice for the
follow-up of neonates who are picked up in newborn screening programs with a
suspicion of isovaleric acidemia.
2.2.3
Molecular basis of IVD
The IVD gene is located on chromosome 15, region q14 → qter (Kraus et al., 1987),
and consists of 12 exons and 11 introns, spanning ~15 kb of genomic DNA (Parimoo
and Tanaka, 1993). Analysis of the IVD gene in patients with symptomatic IVA led to the
identification of numerous missense, nonsense, frameshift-, and splice-site mutations.
The latter cause changes in the intron-exon boundaries of the IVD gene and abnormal
processing of IVD mRNA. Most of these mutations consequently lead to the production
of an inactive or unstable IVD protein (Vockley et al., 1991; Mohsen et al., 1998;
Vockley et al., 2000; Ensenauer et al., 2004). Specific mutations have been prominent
in various ethnic groups, suggesting a founder effect in some populations (Lee et al.,
2007; Lin et al., 2007; Qui et al., 2008; Lee et al., 2010; Vatanavicharn et al., 2011;
Hertecant et al., 2012; Kaya et al., 2012). An earlier proposal to classify IVD mutations
was made by Vockley et al. (1991) in order to devise a genotype-phenotype relation in
IVA, but no clear genotype-phenotype relation was found (Vockley and Ensenauer,
2006).
The absence of a clear genotype-phenotype relation in IVA has been noted in several
subsequent studies. Ensenauer et al. (2004) reported on a mutation c.952A > C
(p.A314V), typically identified via newborn screening. Patients, homozygous for this
mutation, present with a benign to mild form of IVA. Lee et al. (2007) investigated IVA in
14
General introduction and outline of thesis
a Korean population and identified splice-site as well as missense mutations, all
resulting in different phenotypes – 5 patients showed early onset of symptoms and 2
subjects presented with no symptoms that far. Lin et al. (2007) reported on the
involvement of 6 missense mutations [the most common being the c.1208A > G
(p.Y403C)] in the Taiwanese population, which resulted in both mild and severe
phenotypes. The pathogenicity of certain mutations was recently explored with an in
silico analysis of a cryptic splice-site deletion (c.1136_1138þ4delTTGGTGA) in exon 11
found in IVA patients from the United Arab Emirates (Hertecant et al., 2012).
The variation in IVA genotypes only partly explains the variation in the phenotypical
presentation of the patients. Furthermore patients with the same genetic mutation may
widely demonstrate different clinical signs and symptoms. Inappropriate dietary
measures, delayed diagnosis (Vockley and Ensenauer, 2006), modifier genes (Dipple
and Mcabe, 2000) or even epigenetic and polygenetic factors of unknown origin (Turan
et al., 2010) may be responsible for these phenotypical variations.
2.2.4
Clinical aspects
IVA was first characterized by the odour of sweaty feet during periodic illness in the
breath and biological fluids of patients which was attributed to isovaleric acid (Budd et
al., 1967). The disorder was initially classified as having two phenotypic groups, based
on the diverse clinical presentation of the disease. The first IVA group manifested with
an acute neonatal presentation (usually in the first few weeks of life) and non-specific
symptoms, including poor feeding, vomiting, seizures, metabolic acidosis and a reduced
level of consciousness (Tanaka et al., 1966; Budd et al., 1967). A second group of IVA
patients presented with a chronic intermediate clinical profile, characterized by
developmental problems of a variable degree and failure to thrive (Levy et al., 1973;
Shih et al., 1984). Intermittent acute episodes of decompensation accompanied by mild
illness are present in both groups. The patients' survival of the initial metabolic crisis
makes these groups indistinguishable from each other as the disease progresses
(Tanaka, 1990). In addition, a benign to mild IVA phenotype that has been described
suggests that IVA patients may fall within a broad spectrum of clinical presentations
(Ensenauer et al., 2004). Consequently, an updated metabolic classification has been
put forward consisting of a "metabolically severe group" and a "metabolically mild or
intermediate group" (Vockley and Ensenauer, 2006).
Various pathophysiological manifestations accompany IVA and are primarily associated
with the accumulation of isovaleryl-CoA as well as isovaleric acid. The biochemical
mechanisms of these pathological findings are discussed in this chapter in sections
2.2.1 and 4. Both hypoglycemia (due to physiological stress and fasting) as well as
15
Chapter 1
hyperglycemia (in some cases misdiagnosed as diabetic acidosis) have frequently been
observed in IVA patients (Worthen et al., 1994; Erdem et al., 2010). In addition,
hyperlactatemia as well as ketosis are frequently observed in patients during a
metabolic crisis (Tanaka et al., 1966). Furthermore, an unexplained anion gap,
secondary hyperammonemia (discussed in sections 2.2.2 and 5 of this chapter),
hypocalcemia and immunological abnormalities, to varying extents, have been observed
in IVA patients. The immunological features are linked to transient bone marrow
suppression by isovaleryl-CoA, which may result in pancytopenia and isolated
neutropenia and thrombocytopenia (Kelleher et al., 1980; Vockley et al., 2012).
Many patients have a tendency to avoid food rich in protein due to past medical
experiences. IVA patients can also present with acute pancreatitis, myeloproliferative
syndrome, Fanconi syndrome, and cardiac arrhythmias (Arnold et al., 1986; Kahler et
al., 1994; Gilbert-Barness and Barness, 1999). Isolated IVA patients with bilateral
cataract, dwarfism and adrenoleukodystrophy have also been described in the literature
(Duran et al., 1982; Bonilla Guerrero et al., 2008).
Brain damage and neurological
abnormalities are present in the severe forms of IVA, but the related biochemical
mechanism is still poorly understood. Cerebral edema and/or hemorrhage may occur as
a result of untimely or insufficient treatment (Fischer et al., 1981). In such cases, the IVA
patient can progress into a coma and in some instances death (Vockley et al., 1991;
Vockley et al., 2012). Consequently, the success of treatment determines the extent of
the neurological aberrations and clinical features. The outcome may vary from normal
psychomotor development to severe developmental handicaps.
3
Diagnosis of isovaleric acidemia
The routine diagnostic protocol for treatable IEMs has undergone extensive
development in the past decades with sophisticated biotechnology increasingly
available. The development of mass spectrometry as a paramount NBS tool enabled the
timely identification of various organic acidemias, fatty acid oxidation disorders and
aminoacidopathies
in
blood-spot
samples
of
presymptomatic
neonates.
The
identification of medically manageable IEMs, such as IVA, by means of a metabolite
signature before clinical presentation and deterioration of the patient, consequently
offers the possibility of well-timed therapeutic interventions (Dionisi-Vici et al., 2006).
However, the introduction of NBS has also led to the identification of a group of IVApatients with a benign clinical presentation and has forced clinicians and dieticians to
assess each case carefully and to readdress and prescribe a subsequent personalized
treatment regimen.
16
General introduction and outline of thesis
The identification of C5-carnitine, through acylcarnitine profiling in samples of newborns,
heralds the initiation of follow-up specified metabolic screening, which includes organic
acid profiling (Millington et al., 1990; Wilcken et al., 2003). C5-carnitine represents a
mixture of isomers and their presence may be indicative of several conditions, namely,
2-methylbutyrylglycinuria, MADD or the presence of a medicinal artifact such as
pivaloylcarnitine (Vockley et al., 2012). Consequently, the collection of additional
samples (urine, blood card and plasma) should be requested to test specifically for a
possible IEM which is associated with elevated C5-carnitine. Urine samples may have
the odour of sweaty feet as described in section 2.2.4, but this is not the rule for all IVA
patients. The presence of primary diagnostic markers (mostly found in urine), namely,
N-isovalerylglycine and 3-hydroxyisovaleric acid, as well as secondary IVA markers
depicted in Fig. 2 further points to the diagnosis and metabolic status of IVA patients
(Tanaka and Isselbacher, 1967; Tanaka et al., 1968; Vockley et al., 2012). The
identification of IVA at the metabolite level must also include elevated C5-carnitine (as a
mixture of isomers) detected by MS/MS in the urine and blood of patients. The selective
screening procedure should be followed by the measurement of the activity of IVD in
fibroblasts and/or lymphocytes and mutation analysis for definitive diagnosis.
The identification of N-isovalerylglycine via GC-MS analyses (Hine et al., 1986) and/or
isovalerylcarnitine with mass spectrometry (Shigematsu et al., 1996) in amniotic fluid
has been shown to be a reliable tool in the prenatal diagnosis of IVA. Eventually,
mutation analysis of the IVD gene is the best option for conclusive pre- and postnatal
diagnosis. It is highly recommended that families undergo genetic counseling and be
informed about all aspects of IVA including treatment. It is essential to know that an
acute metabolic crisis in IVA patients increases the risk of long-term neurological
abnormalities, as well as other secondary physiological effects, which lead to a poor
quality of life and even death in some cases. However, the patient may also develop the
benign variant of IVA, which may or may not present phenotypically. In any case, the
follow-up and monitoring of patients are vital, and personalized therapeutic intervention
is a particular challenge for each patient, as discussed in the subsequent section.
4
IVA treatment and therapeutic intervention with monitoring
Advances, and to a lesser extent challenges, in the treatment of branched chain amino
acid disorders have emphasized the need for treatment strategies based on the clinical
assessment of each patient and by acting accordingly. Indeed, the monitoring of
biochemical parameters is essential and metabolomics may be a useful tool for the
comprehensive assessment of both treated and untreated patients with branched chain
amino acid disorders with diverse metabolic phenotypes (Knerr et al., 2012).
17
Chapter 1
4.1 Treatment through dietary intervention
The main strategy of dietary intervention and the design of nutritional regimens to treat
organic acidemias, involves: 1) the restriction of one or more nutritional components
from which toxic substances may be produced as a result of enzyme deficiency; 2)
supplementation of potentially deficient nutritional compounds; 3) the elimination of toxic
compounds via the intake of detoxifiers (glycine and L-carnitine are most commonly
used); and 4) administration of pharmacological agents which alleviate the secondary
aberrations of the disease, such as hyperammonemia (Giovannini et al., 1995; Daniotti
et al., 2011).
IVA is one of the metabolic defects which respond well to dietary intervention, such as
limiting the intake of leucine. The prevention or early intervention of a metabolic crisis is
the main objective in the treatment of IVA. The secondary breakdown of endogenous
leucine during metabolic decompensation is inevitable, and consequently leads to the
accumulation of isovaleryl-CoA (as described in section 2.2 of this chapter). Stabilization
of IVA patients is achieved through the intake of glucose, and subsequently limited
ingestion of proteins, in particular those high in leucine.
Apart from these general guidelines in the treatment of IVA, some specific clinical
actions are recommended to physicians faced with life-threatening events affecting IVA
patients. Thus, patients suffering from metabolic decompensation normally require
immediate hospitalization and a recommended glucose infusion of 8 mg/kg.min, when
needed with the simultaneous use of intravenous insulin, under the primary supervision
of a pediatrician. Depending on the clinical evaluation of the patient, the protein intake
may be returned to the originally prescribed level after 24 hours. It is generally agreed
that a low protein diet involves maximum protein intake of 1.5 g/kg body weight/day. The
latter is essential for adequate growth and development (Vockley and Ensenauer,
2006).
To date, no biomarkers for the therapeutic monitoring of IVA patients are available
(Vockley et al., 2012). However, we anticipate that future research will identify
biomarkers to indicate the metabolic status of IVA patients and adapt their treatment.
Consensus protocols for organic acidemias, including IVA, and urea cycle defects
(UCDs) are currently being developed by the European Registry and Network for
Intoxication-type Metabolic Disorders (E-IMD) (http://www.e-imd.org) in order to facilitate
the development of strategies to evaluate and determine the metabolic status of
patients. The E-IMD consortium, which was established in 2011, has made substantial
progress in assessing the diagnosis, treatment and follow-up of patients with related
diseases and will subsequently contribute to the design of comprehensive guidelines to
deal with the corresponding metabolic defects.
18
General introduction and outline of thesis
4.2 Detoxification options for IVA patients
Most IVA patients respond positively to prescribed detoxifiers (glycine and L-carnitine),
with optimal conjugation of isovaleryl-CoA, the accumulating primary metabolite of this
condition. The clearance of grossly elevated isovaleryl-CoA is achieved through
conjugation with glycine and the formation of N-isovalerylglycine, which is excreted by
the kidneys. Several studies have shown the benefit of glycine treatment, without
adverse implications for IVA patients (Cohn et al., 1978; Yudkoff et al., 1978; Naglak et
al., 1988). In contrast, some reports emphasized the fact that the in vivo glycine-Nacetylating capacity may vary among individuals and that some patients are prone to
have episodes of hyperglycinemia, resulting in encephalopathy during continuous
glycine treatment (Duran et al., 1979; De Sousa et al., 1986).
Subsequently,
supplementation of 150–300 mg/glycine per kg body weight per day is the
recommended dosage for IVA patients, but monitoring of plasma glycine levels (aim at
levels of 200–400 μM) must be carried out to prevent unwanted side effects of the
treatment (Wappner and Gibson, 2006).
L-carnitine is an essential cofactor in fatty acid oxidation where it acts as a carrier of
acyl groups to transport fatty acids across the mitochondrial inner membrane and also
functions as a modulator of the acyl-CoA/CoA ratio (Bremer, 1983). Because carnitine
plays a vital role in normal CoA-homeostasis within the mitochondria, it is involved in the
treatment of various organic acidemias. Its benefits in IVA include the prevention of
systemic carnitine depletion as well as the formation of isovalerylcarnitine, which is
safely excreted in the urine. No reports of secondary clinical complications in the
administration of L-carnitine could be found (Stanley et al., 1983; Roe et al., 1984). A
dose of 100 mg/kg per day has now been recommended to avoid depletion of free
carnitine and to maximize isovalerylcarnitine formation (Wappner and Gibson, 2006).
The use of glycine and L-carnitine in combination improved the biochemical profile of
IVA patients, for example, by reducing ketosis and acidosis during episodes of
metabolic decompensation. The pros and cons of separate and combined use of
supplementation have been widely debated. Various studies have been conducted to
determine the appropriate dose of L-carnitine and glycine needed for effective treatment
of IVA patients (Berry et al., 1988; De Sousa et al., 1986; Mayatepek et al., 1991; Van
Hove et al., 1994). The conclusion in the majority of these studies was that an increase
in L-carnitine dosage initially enhanced N-isovalerylglycine formation, which declined
over a 24-hour period. More recent studies concluded that L-carnitine in combination
with glycine results in the most appropriate long-term treatment of IVA patients (Itoh et
al., 1996; Vockley and Ensenauer, 2006). The clinical presentations of the patients
enrolled in these studies varied, which again emphasized the need of a personalized
approach in L-carnitine and glycine treatment of individual patients. It is anticipated that
19
Chapter 1
the comprehensive investigation by the E-IMD consortium may shed light on the use of
supplementation and its involvement in the phenotypical presentation of IVA.
4.3 Nutritional deficiencies
The restricted protein intake and high synthetic carbohydrate intake implies a diet with
vegetarian-like properties. Dedicated dietary formulas (such as leucine-free amino acid
mixtures) are available for IVA patients, but their use is limited wherever health
economics restrict the use of expensive dietary substituents or supplements. The
alternative, a restricted protein diet, results in amino acid deficiencies and a reduced
intake of vitamins, minerals and polyunsaturated fatty acids (PUFAs) (Giovannini et al.,
1995). Loots et al. (2007) also indicated that IVA patients may suffer from amino acid
depletion due to acylation of these essential biomolecules. They proposed that the
optimum benefits for the patients are a strict leucine-free diet with additional essential
amino acids (including glycine) and added intake of L-carnitine. Patients with organic
acidemias, including IVA, may develop antioxidant depletion and reduced intracellular
glutathione. Therefore it was recommended that organic acidemia patients should
receive antioxidant supplementation in their routine management (Atkuria et al., 2009).
Further investigations of patients with protein-related deficiencies – for example
phenylketonuria, urea cycle deficiencies, maple syrup urine disease (MSUD),
methylmalonic acidemia, homocystinuria and other amino acid-related disorders –
demonstrated deficiencies in omega-6 and omega-3 polyunsaturated fatty acids and
their related biological products, because of the restricted dietary intake of the fatty
acids and their precursors in the form of linoleic acid and alpha-linolenic acid
(Vlaardingerbroek et al., 2006, Fekete and Decsi, 2010).
4.4 Administration of pharmacological agents to alleviate secondary
biochemical abnormalities
Various supplementation options have recently been proposed to alleviate secondary
pathophysiological effects of IVA. The use of N-carbamylglutamate to activate carbamyl
phosphate synthetase 1 and thereby reduce elevated ammonia levels was successfully
demonstrated by Kasapkara et al. (2011). Furthermore, the administration of creatine
has been shown to act as a "neuroprotector" in various neurological diseases (Matthews
et al., 1998). It has recently been shown that creatine prevents Na+,K+-ATPase
inhibition caused by isovaleric acid resulting in normal neurological function in an animal
model. Consequently, creatine may be beneficial as a "neuroprotector" and considered
as a future therapeutic agent for IVA (Ribeiro et al., 2009). The optimal dosage of Ncarbamylglutamate and creatine to treat pathophysiological effects and the development
20
General introduction and outline of thesis
of chaperones to improve IVD activity is still under investigation and will probably be
part of personalized medicine of individual patients.
The biochemical stabilization of enzymes through the use of pharmaceutical
chaperones is another promising treatment option for IEMs. These chaperones may
restore the native configuration of IVD, thereby increasing their residual activity. Their
use in organic acidemias such as IVA is currently being investigated (Gregersen, 2006).
Finally, IVA patients affected by IVD gene mutations that give rise to a stop codon and
hence a truncated enzyme protein may benefit in the near future from drugs which may
result in an enhanced read-through. Currently a trial in this area on a Europe-wide basis
is being carried out in a group of patients with methylmalonic aciduria (Sánchez-Alcudia
et al., 2012).
5
Pathophysiological complications of IVA
Isovaleric acidemia is caused by the dysfunctioning of isovaleryl-CoA dehydrogenase.
Various secondary pathophysiological events result from this primary lesion and have
become characteristic of the disorder. Lactic acidosis, ketosis, hyperammonemia and
immunological abnormalities are typical manifestations of the acute presentation of the
disease. Most of these symptoms can be managed therapeutically via different
treatment options, which in general limit the number as well as the severity of the
episodes
of
metabolic
decompensation
(Vockley
et
al.,
2012).
Secondary
hyperammonemia, which is a prominent biochemical feature of IVA, is also observed in
other organic acidemias that may be accompanied by neurological dysfunction such as
propionic acidemia and methylmalonic acidemia.
This biochemical aberration is presumed to be due to the inhibition of N-acetylglutamate
synthase (NAGS) by accumulating isovaleryl-CoA (or other short-chain acyl-CoAs)
and/or intracellular depletion of acetyl-CoA, which subsequently leads to reduced Nacetylglutamate synthesis and consequent impairment of the urea cycle (Coude et al.,
1979; Stewart and Walser, 1980; Lehnert, 1981b). NAGS is responsible for the
production of N-acetylglutamate (NAG), which activates the initial rate-limiting enzyme,
carbamyl phosphate synthetase 1 (CPS), of the urea cycle. Prolonged secondary
hyperammonemia can lead to irreversible neurological damage and account for some of
the pathogenic occurrences in IVA (Cagnon and Braissant, 2007). Patients with a urea
cycle defect usually have markedly increased levels of the amino acid glutamine, which
supposedly contributes to the neurometabolic damage. Excessive formation of
glutamine in IVA (and other classical organic acidemias) does not take place, probably
as a consequence of a disturbed Krebs cycle that limits the availability of 2ketoglutarate, the original precursor of glutamine (Meijer et al., 1990). Nevertheless, the
21
Chapter 1
prevention of hyperammonemia in IVA and other organic acidemias is of prime
importance to improve the quality of life of affected patients.
The outcome of IVA patients who were diagnosed following an episode of metabolic
decompensation is not entirely satisfactory. It is expected that the implication of largescale newborn screening will improve this aspect of the disease. However, it is still too
early to predict that subsequent episodes following the NBS-diagnosis will cease to
occur, and many efforts will be needed to find the best personal treatment regimen for
every patient.
6 Metabolomics: A multidisciplinary data-driven strategy to obtain
information contained within a diverse biological system
All aspects of IVA discussed thus far dealt with well-established approaches used to
investigate and characterize inborn errors of metabolism. Metabolomics, the third
member of the initial "-omics" triplet (consisting of genomics and proteomics apart from
metabolomics), became recognized as an important emerging field of scientific research
about a decade ago (Goodacre, 2005; Goodacre, 2010). Wikoff et al. (2007) provided
the first proof-of-concept that metabolomics could expand the range of metabolites
associated with inborn errors of metabolism as shown for propionic acidemia (PA) and
methylmalonic acidemia (MMA), and concluded that metabolomics might be useful in
the diagnosis and evaluation of patients suffering from these diseases. It was therefore
logical to include a metabolomics approach as part of an integrated investigation of
South African cases of IVA. It is beyond the purpose of this thesis to present an in-depth
review of metabolomics technology as it has already been well covered in several
monographs (Lindon et al., 2007; Weckwerth, 2007; Griffith, 2008) and recent reviews
(D'Alessandro et al., 2012; Beger and Colatsky 2012; Zhang et al., 2012; Bartel et al.,
2013; Brennan, 2013). The focus here will be on the topicality of a metabolomics
approach to investigate inborn errors of metabolism and its potential to contribute to the
further development of predictive laboratory medicine.
6.1 A metabolomics approach in the study of IEMs
Clinical chemists anticipate that the application of metabolomics will improve
researchers' and clinicians' knowledge of inborn errors of metabolism and their
treatment (McCabe, 2010). The main purpose of metabolomics is to identify as many
metabolites as possible that are altered due to a known perturbation within the biological
system of interest, and which consequently leads to a greater understanding of the
biochemical and clinical relevance of the metabolites in the altered state. The
importance of a standardized metabolomic protocol has been emphasized by various
22
General introduction and outline of thesis
researchers in the field. This approach consists of 1) the careful selection of defined
groups (e.g. patients versus controls); 2) the type of biological samples to be used (e.g.
blood, urine, sputum or tissue); 3) the choice of methods, which include sample
preparation and the selection of instrumentation – such as nuclear magnetic resonance
spectrometry and hyphenated mass spectrometry (MS) – for data acquisition; 4) the
procedures used for data processing via deconvolution and statistical analyses – for
example, univariate analyses or multivariate analyses such as principal component
analysis and partial least-squares-discriminant analysis (PLS-DA); and 5) the
interpretation of the information derived from the data analysis in relation to the
biological system being investigated (Goodacre et al., 2007).
This protocol includes several aspects which are familiar to biochemists involved in the
study of IEMs. Those who study these disorders are normally comfortable with most of
the steps in the standardized metabolomics protocol and are used to investigate
disease in relation to genotype-phenotype correlations and the consequent clinical
manifestations (McCabe, 2010). However, the analyses required to reveal the
information in complex data sets are not typically part of traditional research in IEMs
(Goodacre, 2005). The need for timely identification of novel and treatable metabolic
disorders, however, has fast-tracked the development of sensitive acquisition and
identification of biomolecules in specimens of medical interest. This became the core of
NBS, as discussed above, and the use of tandem MS was designed for high-throughput
application in the screening for various IEMs. The application of MS as a powerful tool
for diagnostic purposes inadvertently laid the foundation for "targeted metabolomics"
and the beginning of unique metabolic profiling for various types of deviations from
normality related to age, gender and disease in different life forms (McCabe, 2010).
Already more than a century ago, Sir Archibald Garrod, a pioneer of IEM studies,
postulated that individual IEMs were due to one faulty gene resulting in the production of
a defective enzyme and consequently a specific metabolic disorder – in his case it was
the description of alcaptonuria. Recent findings describe variations within the clinical
and pathophysiological presentation of metabolic disorders and suggest multifactorial
involvement in many IEMs, including IVA (see above). The comprehensive study of
healthy subjects, MMA and PA, revealed significant differences in the presence and
absence of metabolites among the three groups (Wikoff et al., 2007). The untargeted
metabolomics approach established proof-of-concept and the potential benefits of
metabolomics in the diagnosis of metabolic disorders, providing information on
phenotypical diversity and the clinical monitoring of patients. The diagnosis of classical
MMA and PA via biomolecular analyses is not difficult in the field of IEMs, but diagnosis
of complex metabolic disorders, without invasive techniques and extensive genetic
screening, is a great challenge to the clinical biochemist. The example of deficiencies in
the respiratory chain defects (RCDs) will be discussed below to illustrate this point.
23
Chapter 1
Over 100 different RCDs – with an incidence of 1:5 000 to 1:10 000 among newborns –
may manifest at any age (see reviews by Smeitink et al., 2006 and Haas et al., 2008).
The multi-systemic involvement of different organs and non-specific symptoms limit the
differential diagnosis and understanding of the pathophysiology involved. Inadequate
knowledge of the consequences of the defects within the body results in poor
therapeutic intervention and unpredictable quality of life for the sufferers (Suomalainen,
2011). These factors inspired researchers to search for the metabolic fingerprint for
RCDs.
Suomalainen
(2011)
recommended
several
approaches,
including
metabolomics, for the identification of suitable biomarkers. Reinecke et al. (2012)
constructed a comprehensive metabolite profile of the carbohydrates, amino acids and
fatty acids involved in the catabolism of 39 RCD patients, which emphasized the
biochemical complexity of these disorders. Their study proposed that the identification of
a biosignature via chemical pattern recognition, rather than one or a few specific
biomarkers, holds the key to a potential non-invasive screening for RCDs. Smuts et al.
(2012) investigated subsections of the metabolome of selected RCD patients using a
differential analytical protocol, which included GC-MS, ESI-MS and NMR. They also
focused on one subset of RCDs and consequently improved on the selection of certain
patients. Specific medical procedures and treatment with the aid of a metabolomicsdriven approach were also derived. The value of metabolomics to identify the
biosignatures in RCDs in terms of metabolic markers was a further illustration of the
proof-of-concept through this study of a complex set of IEMs (Smuts et al., 2012), which
concurs with the view that metabolomics investigations of multifactorial diseases should
focus on studying complex and dynamic biomarker patterns rather than on single
biomarkers (Van der Greef and Smilde, 2005).
This brief overview of the first pioneering metabolomics studies of IEMs indicates its
value for a further understanding of these diseases and may eventually contribute to the
identification of biochemical mechanisms involved in these disorders, as well as their
corresponding pathophysiological implications. These features are not yet well
understood for autosomal recessive disorders, and subsections of this thesis will
address some of these features through the metabolomics investigation of South African
cases of IVA.
6.2 Metabolomics and laboratory medicine
The potential benefits of metabolomics are progressively being recognized as also
affecting laboratory medicine which is defined as that part of medicine in which
specimens of tissue, fluid or other body substances are examined outside of the
patient's body (D’Alessandro et al.; 2012). This can be related to three innovative
applications of metabolomics: 1) the generation of new knowledge and an increased
24
General introduction and outline of thesis
understanding of metabolism and its regulation; 2) improvement of important areas in
contemporary laboratory medicine, such as patient risk assessment, prediction of
disease development and the monitoring of treatment strategies; and 3) the introduction
of personalized medicine based on individualized phenotyping.
6.2.1
New knowledge
The novel and useful features of metabolomics have been identified in various
biochemical and clinical conditions as described above. The investigation and detection
of biomarkers by metabolic profiling within the metabolome have been pursued with
limited biological information, as well as with known biology, on the basis of targeted
and untargeted analyses. Both approaches can result in the comprehensive
identification of new biomarkers with the potential for the diagnosis of disease, and for
evaluating its severity and treatment (Mamas et al., 2011). Metabolomics is thus
expected to play a key role in 1) detecting patterns of metabolites that may be
unexpected but important in explaining disorders, and reveal mechanisms of disease
and consequently the phenotypes within various subject groups; 2) predicting the effects
of drugs, their efficacy or toxicity and therefore how to customize treatment protocols;
and 3) non-invasive to minimal invasive investigations of biological abnormalities
through the study of biological fluids and which have already brought benefits in several
fields, for example, paediatrics (Baraldi et al., 2009). At the Metabomeeting held in
Manchester, UK, in 2012, Reinke and Broadhurst (2012) acknowledged that
metabolomics may be used as a basis for various hypotheses to broaden scientific
knowledge on several levels. Metabolomics may also reveal the importance of
regulation of the metabolic steps within a biological system that are vital for cell
organization and functionality (Vangala and Tonelli, 2007).
Furthermore, metabolomics offers various benefits which improve on genomics and
proteomics in several ways. For example: 1) there are estimated to be ~3 000
metabolites that exist to be examined in metabolomics studies compared with the much
larger number of variables present in other "-omics" data sets; 2) its likely application in
clinical chemistry appears to be imminent due to progress in non-invasive sample
collection; 3) the technology may be of use in animal models in which biomarkers of
clinical relevance to a particular disease or toxicology are evaluated; and 4) the
metabolic state of a biological system is reflected in changes in metabolite levels, and
so mirrors alterations in the phenotype with the onset, for example, of disease, which is
determined by the genotype in combination with external factors. Thus, metabolomics
facilitates the elucidation of the clinical pathology of disease as in the case of IEMs,
which results in the characterization of unique phenotypes. Timely and targeted
treatment and medical intervention can proceed with the help of a customized
25
Chapter 1
metabolomics approach (Vangala and Tonelli, 2007; Shlomi et al., 2009). This was
highlighted by Wikoff et al. (2007) and Reinecke et al. (2012), who reported that diverse
phenotypes exist within simple as well as complex IEMs (discussed above). This
phenomenon is still poorly understood, but the evidence from metabolomics is already
contributing to a rethinking of the traditional concept of one phenotype, one genotype.
Future work should aim at extending the current metabolomics models to recreate a
comprehensive metabolic network with leading researchers for example the Edinburgh
Human Metabolic Network (Ma et al., 2007) – and subsequently identify all primary and
secondary pathways of relevance to human health and disease. Predictive metabolic
pathways and the corresponding biomarkers should reveal the real biological activity of
activation or inhibition of selected pathways. Evidently, the need for complex
computational methods for solving such an integrated metabolic network, which may
further implicate alterations on the systems level (including genomic, proteonomic and
metabolomic information) will most probably gain importance in the future (Van der
Greef and Smilde, 2005; Shlomi et al., 2009).
6.2.2
Prediction of disease development and monitoring of treatment
Whitfield et al. (2004) and Grieger et al. (2008) assessed the value of metabolomics and
its clinical application and indicated its benefits to medicine. The current rapid
development in metabolomics has made it possible to describe the "metabotype" in
relation to the genotype of individual subjects. Intermediate phenotypes and disease
aetiology can be continuously assessed biochemically and may provide details on the
pathways potentially affected. Grieger et al. (2008) described this process as a
"fundamental read-out of the physiological state of the human body". Genotype variation
does not affect a single step in the metabolism of lipids, carbohydrates or amino acids,
but plays a more intricate role in a cascade of the metabolic conversions and
modifications that consequently affect the molecular mechanisms that underlie disease.
Once these factors that are fundamental to health and disease are properly addressed,
we may use the technology of metabolomics for drug development and nutritional
intervention to tackle different clinical problems. This in turn may offer the prospect of
further developments in predictive laboratory medicine (Fig. 4) (Grieger et al., 2008).
A metabolomics approach has led to several applications in the field of clinical diagnosis
and pharmacological research. It can be employed in pre-clinical trials to ascertain
biomarkers related to toxicity and efficacy of pharmacological agents, which can be
evaluated subsequently and monitored in clinical trials. Biomarkers are useful in locating
a point(s) in a pathway which might be the cause or effect of a particular disease or
abnormality. This knowledge may be useful in the development of a drug to correct or
26
General introduction and outline of thesis
treat this cause or effect and also lead to the identification of novel targets associated
with drug intervention (Nörstrom and Lewensohn, 2010).
The broader and exciting aspect of a metabolomics approach, in the post-genomic era,
is that it can produce not only metabolic profiles but also intricate metabolic maps which
can be used in different fields of medicine, including nutrition, in health and disease (Fig.
4) (Watkins et al., 2001). The complex interaction between exogenous and endogenous
nutrients and vital metabolic processes can be examined with this approach, which may
help in the construction of the "dietary biosignature" observed in the biofluids of
individual subjects (German et al., 2004). Go et al. (2003) and Milner (2003) reported
that chronic diseases can have both a dietary and a genetic component. Metabolomics
has been further applied to establish the relevance of metabolic control in relation to
disturbances (deficiencies or excesses) of dietary components. The value of
metabolomics in relation to nutrition has been demonstrated in several investigations on
nutritional substances, such as the metabolism of ethyl glucoside (Teague et al., 2004)
and isoflavones (Solanky et al., 2003), which are present in some diets.
Fig 4: Illustration of the effect of treatment intervention after diagnosis of treatable IEMs with
emphasis on the development of an individualized approach (indicated by the dashed oval), made
possible by a metabolomics investigation. (This representation is based on that of Nörstrom and
Lewensohn, 2010).
The comprehensive analysis of different classes of metabolites has also led to
specialized metabolomics approaches that are useful in different aspects of medicine.
For example, lipidomics, a subcategory of metabolomics that focuses on lipid
metabolism, is used as a means to understand the genome (e.g. polymorphisms), as
well as post-genetic effects induced by pathogens, drugs, nutrition and toxins. This field
of research consists of the analysis of various lipid classes which are responsible for
cellular structure and the functionality of complex signal transduction systems.
27
Chapter 1
Furthermore, lipids play a vital role as a source of energy in biological systems (German
et al., 2007). Several lipidomics studies indicate that disease, nutritional status and drug
applications have an influence on the functionality (genetically and biochemically) of
peroxisomes and mitochondria and consequently lead to altered levels of several types
of lipids, including polyunsaturated fatty acids, glycolipids, phospholipids and
triacylglycerols (Whitfield et al., 2004).
6.2.3
Personalized medicine
The arrival of the "-omics" research applications has shown promise in the development
of personalized basic health assessment, in the prevention of disease and of health
care.
Many
researchers
believe
that
these
"-omics"
technologies,
including
metabolomics, will effectively address today's shortcomings in the clinical support of
patients. However, gaps exist between the discovery and implementation of new
knowledge in daily medical practice, and consequently in the understanding of genetic
and metabolic differences among individuals. The development of these innovative and
efficient technologies has resulted in a paradigm shift from classical clinical disciplines –
which are based on reliable diagnostic information – to a broader scope of investigation,
which consists of the assembly of biological maps (intricate metabolic pathways) which
will ultimately result in the novel biomarker identification in health and disease (Plebani
and Lippi, 2013).
The dynamic state of the metabolome, in contrast to the genome, has resulted in the
recognition of common genotypes with multiple phenotypes due to external factors of
unknown origin (Baraldi et al., 2009). Metabolomics can therefore contribute further to
the evaluation of past and future perspectives and consequences of the metabolic
status of the metabolome of all living organisms. Aspects of the relationship between
metabolomics and personalized medicine will thus be highlighted in the thesis.
Ultimately, the insight and impact of contemporary metabolomics testify to the
pioneering vision of Archibald Garrod on individuality in human health and in IEMs in
particular (Garrod, 1909):
"To our chemical individualities are due our chemical merits as well as our
chemical shortcomings, and it is very nearly true to say that the factors which
confer upon us our predispositions to, or our immunities from, the various
mishaps which are spoken of as disease, are inherent in our very structures,
and even in the molecular groupings which confer upon us our individualities,
and which went to the making of the chromosomes from which we sprang."
28
General introduction and outline of thesis
6.3 Challenges and opportunities in metabolomics investigations of IEMs
It should be noted that a metabolomics investigation of an IEM will present with several
challenges as well as opportunities that are common to metabolomics investigations in
general, but are also unique to investigations of these diseases. Three such challenges
and opportunities are highlighted in this section, as they are of particular relevance to
the present investigation of IVA.
In general, metabolomics is a field of research which, in its most simplified form, is
linked to the traditional disciplines of biology, chemistry and statistics in which their
respective experts actively collaborate to explore metabolic processes in biological
systems (Fig. 7). An example is the interactions between, or the consequences of,
stimuli (such as chemicals or disease) on metabolism as reflected by the resulting
metabolite profiles.
Fig 5: A model to illustrate the transdisciplinary aspect of metabolomics research (reproduced with
permission after personal communication with M. van Reenen).
Fig. 5 shows that the research questions addressed in metabolomics are predominantly
formed from a biological or clinical point of view. The response to such questions often
requires an untargeted metabolomics approach. For untargeted metabolomics
investigations, inputs from two very different fields of specialization are essential: highly
29
Chapter 1
sophisticated analytical chemistry and equally highly specialized, statistically based
bioinformatics and related information technologies. This is clearly emphasized in the
definition used by Harrigan et al. (2005):
"Metabolomics involves the acquisition of a metabolome dataset of sufficient
chromatographic and spectral richness and resolution for multivariate statistical
analysis and for metabolite identification and quantification."
Katajamaa and Oresic (2007) more recently emphasized the biological aspect, defining
metabolomics as
"a discipline dedicated to the global study of metabolites, their dynamics,
composition, interactions, and responses to interventions or to changes in their
environment, in cells, tissues, and biofluids."
As a consequence, information emerging from metabolomics is solution-driven and can
only be achieved through transdisciplinary collaboration. This viewpoint opens the
possibility of defining various challenges and opportunities to most metabolomics
investigations, and specifically so in the field of IEMs.
•
Some minimum requirements for experimental design and reporting of data and
findings have been defined for metabolomics investigations (Goodacre et al., 2007).
In this regard, sample collection and preparation present with unique challenges not
to produce biases due to the selection of experimental groups or to the choice of
the metabolome to be analyzed (Dunn and Ellis, 2005). This is a particular
challenge in metabolomics investigations of IEMs, given the limited number of
cases which are typically available for these studies, as well as the special
requirements to obtain reliable controls for these investigations (Barshop, 2004).
Although the IVA patient group available for the investigation reported in this thesis
was relatively small, it was nevertheless seen as an opportunity to embark on a
metabolomics approach to understand this IEM further.
•
Transdisciplinary
research
generates
exciting
opportunities:
metabolomics
investigations not only present with complex challenges to the biological and clinical
specialists in such studies, but also to the analytical chemists and statisticians.
However, these challenges also open up opportunities to these experts for further
new supporting approaches to generate and analyse the experimental data. This is
clearly illustrated by the novel approaches to develop original models to assess
analytical aspects such as repeatability in the generation of metabolomics data
(Van Batenburg et al., 2011) or the statistical analysis of metabolomics data
(Smilde et al., 2005). Although these challenges are beyond the expertise of the
biologist or clinician, it can be anticipated that an investigation as presented here
could contribute to such novel developments.
30
General introduction and outline of thesis
•
Application: Metabolomics has recently been hailed as opening a new frontier in
paediatric research, which inevitably includes the clinical assessment of infants
suffering from an IEM (Carraro et al., 2009). Such potential applications that could
emanate from knowledge of metabolomics are generally referred to as examples of
translational research. Such research has received focus with regard to research
activities in medicine and seems to be gaining support on the evidence of the
funding it generates (Woolf, 2008). The aim of translational research implies
bringing "research into practice" (Woolf, 2008). The "bench-to-bedside" (Woolf,
2008) approach does, however, differ with regard to the composition of the
research team. Translational research tends to remain multidisciplinary, whereas
fields such as metabolomics require transdisciplinary teams. Although translational
research is beyond the scope of the present investigation, the new knowledge
gained through the metabolomics study of IVA holds the promise of being applied
to the benefit of patients suffering from this disease.
7
Outline of this thesis
The main goal of this thesis was to develop an integrated approach to study IVA
including genetic, enzymatic and metabolic assessments. This study therefore
expanded on these objectives and included metabolomics as part of the integrated
approach to improve our understanding of IVA. It was envisaged that this study would
contribute to a change in the paradigm that metabolic defects should be considered as
diverse, multifactorial diseases rather than deficiencies of the one enzyme, one
phenotype kind. Fig. 8 outlines the integrated approach towards the investigation of IVA
and indicates how information was obtained to develop predictive laboratory medicine
for IVA that may be applicable to all treatable IEMs.
31
Chapter 1
Figure 6: A schematic representation of the study design and outcome of the integrated approach
to predictive laboratory medicine.
In Chapter 2 IVA patients from South Africa were characterized via clinical and
biomolecule profiling, IVD gene sequencing and determining the IVD enzyme activity
with a novel approach. A single homozygous mutation (p.G123R) in all patients was
identified which was found to result in an inactive protein, with no detectable residual
IVD activity. The presence of a diverse phenotype within this genetically homogeneous
group was confirmed, which may be attributed to differential treatment regimes, delayed
diagnoses of patients and even epigenetic and polygenetic factors.
Chapters 3 and 4 discuss the use of metabolomics as an investigative tool in a
homogeneous IVA population. Chapter 3 consists of the development of the CONCA
(concurrent class analysis) model, a novel multivariate dimension-reducing technique in
which biomarker differences between untreated IVA patients, treated IVA patients and
control subjects were identified. Chapter 4 is an untargeted metabolomics investigation
in which untreated IVA patients, treated IVA patients, obligatory heterozygotes, and
children and adult control subjects, were compared with various multivariate statistical
applications including CONCA, principal component analysis (PCA) and partial leastsquares-discriminant analysis (PLS-DA) in order to determine variables important in
discrimination (VIDs). Three univariate methods (ES, t-tests and Mann-Whitney tests)
were also included to assess the significance of variation of components of the
respective metabolite profiles in relation to the perturbation being considered. Major and
minor metabolites associated with IVA as well as with secondary conditions of IVA, such
as ketosis, could be clearly identified. Various biomarkers as a result of treatment of IVA
were also identified, which established that the use of personalized therapeutic
32
General introduction and outline of thesis
intervention is needed for individual patients. The obligatory carriers could also be
separated from adult control subjects due to minor excretion of IVA-related metabolites.
Organic acidemias have various secondary biochemical consequences, for example,
lactic acidosis, ketosis, involvement of the liver and hyperammonemia. In Chapter 5 we
report the occurrence of secondary hyperammonemia in IVA as well as other organic
acidemias, where short-chain and short-branched chain acyl-CoAs accumulate. The
urea cycle facilitates the elimination of NH3 via the formation of urea, a non-toxic
metabolite, which is excreted in urine by the kidneys. The initial steps of this cycle are
important in the primary regulation of this pathway. The formation of N-acetylglutamate
via N-acetylglutamate synthase (NAGS) is needed for the activation of carbamylphosphate synthetase (the first and rate-limiting step of the urea cycle). We established
that various short-chain acyl-CoAs act as inhibitors and/or substrates of purified NAGS,
in vitro. The latter explains, and also raises the question of the involvement of these
cumulative CoA esters in the occurrence of secondary hyperammonemia in different
organic acidemias. An additional outcome was the development of a NAGS enzyme
assay described in Chapter 6. This validated assay was used to measure NAGS activity
in mouse liver samples. NAGS knockout mouse liver samples showed no activity,
consistent with NAGS deficiency.
The metabolomics investigation led to the identification of diet-related metabolites.
These findings motivated the examination of some aspects of the nutrient status in
treated IVA patients. Therapeutic intervention and the dietary regimen of IVA and of
other amino acid-related organic acidemias consist primarily of a low protein, high
carbohydrate diet. Various secondary effects of such a diet have been described in the
literature for patients with amino acid-related disorders. Deficiencies in essential fatty
acids, vitamin B12 and other vitamins and minerals have been observed (Robinson et
al., 2000; Vlaardingerbroek et al., 2006; Fekete and Decsi, 2010). Chapter 7 addresses
underlying of nutritional insufficiency in particular deficiencies in functional vitamin B12
and polyunsaturated fatty acids, in treated IVA patients. This chapter emphasizes the
fact that additional monitoring is required in these patients where a protein-restricted
diet is applied.
In the final chapter (Chapter 8), a comprehensive discussion of the findings presented
in this thesis is addressed, including proposals for further detailed investigations on IVA.
References
Arnold WC, Brewster M, Byrne WJ, Booth B. 1986. Fanconi syndrome in a patient with
a variant of isovaleric acidemia. Int J Pediatr Nephrol 7:95-98.
33
Chapter 1
Atkuria KR, Cowanb TM, Kwanc T. et al. 2009. Inherited disorders affecting
mitochondrial
function
are
associated
with
glutathione
deficiency
and
hypocitrullinemia. Proc Natl Acad Sci USA 106:3941-3945.
Baraldi E, Carraro S, Giordano G, Reniero F, Perilongo G, Zacchello F. 2009.
Metabolomics: moving towards personalized medicine. Ital J Pediatr 35:30-34.
Barshop BA. 2004. Metabolomic approaches to mitochondrial disease: correlation of
urine organic acids. Mitochondrion 4:521-527.
Bartel J, Krumsiek J, Theis FJ. 2013. Statistical methods for the analysis of high
through-put metabolomics data. Comp Struct Biotech Jour http://dx.doi.org/
10.5936/csbj.201301009.
Bartlett K, Ng H, Leonard JV. 1980. A combined defect of three mitochondrial
carboxylases presenting as biotin-responsive 3-methylcrotonyl glycinuria and 3hydroxyisovaleric aciduria. Clin Chim Acta 15:183-186.
Battaile KP, Nguyen TV, Vockley J, Kim JP. 2004. Structures of isobutyryl-CoA
dehydrogenase and enzyme-product complex. J Biol Chem 279:16526-16534.
Beger RD, Colatsky T. 2012. Metabolomics data and the biomarker qualification
process. Metabolomics 8:2-7.
Bergen BJ, Stumpf DA, Haas R, Parks JK, Eguren LA. 1982. A mechanism of toxicity of
isovaleric acid in rat liver mitochondria. Biochem Med. 27:154-160.
Berry
GT,
Yudkoff
M,
Segal
S.
1988.
Isovaleric
acidemia:
medical
and
neurodevelopmental effects of long-term therapy J Pediatr 113:58-64.
Bonilla Guerrero R, Wolfe LA, Payne N et al. 2008. Essential fatty acid profiling for
routine nutritional assessment unmasks adrenoleukodystrophy in an infant with
isovaleric acidaemia. J Inherit Metab Dis 31:S453-6.
Bosch AM, Abeling NG, IJlst L et al. 2011. Brown-Vialetto-Van Laere and Fazio Londe
syndrome is associated with a riboflavin transporter defect mimicking mild
MADD: a new inborn error of metabolism with potential treatment. J Inherit
Metab Dis. 34:159-164.
Bremer J. 1983. Carnitine-metabolism and functions. J Physiol Rev 63:1420-1480.
Brennan L. 2013. Metabolomics in nutrition research: current status and perspectives.
Biochemical Society Transactions 41:670-673.
Budd MA, Tanaka K, Efron ML, Isselbacher KJ. 1967. Isovaleric acidemia: clinical
features of a new genetic defect in leucine metabolism. N Eng J Med 277:321327.
Cagnon L, Braissant O. 2007. Hyperammonemia-induced toxicity for the developing
central nervous system, Brain Res Brain Res Rev 56: 183-197.
Carraro S, Giordano G, Reniero F, Perilongo G, Baraldi E. 2009. Metabolomics: A new
frontier for research in pediatrics. J Pediatr 154, 638-644.
34
General introduction and outline of thesis
Carrozzo R, Carlo Dionisi-Vici C, Steuerwald U et al. 2007. SUCLA2 mutations are
associated with mild methylmalonic aciduria, Leigh-like encephalomyopathy,
dystonia and deafness. Brain 130: 862-874.
Chuang DT, Wynn RM, Shih VE. 2012. Branched chain organic acidurias in: Valle D,
Beaudet A, Vogelstein B, Kinzler KW, (Eds) The Online Metabolic and Molecular
Bases of Inherited Disease, Part 8 McGraw-Hill, www.ommbid.com (accessed
on 2 October 2012).
Cohn RM, Yudkoff M, Rothman R, Segal S. 1978. Isovaleric Acidemia: Use of glycine
therapy in neonates. N Engl J Med 299: 996-999.
Coude, FX, Sweetman L, Nyhan WL. 1979. Inhibition by propionyl-coenzyme A of Nacetylglutamate synthase in rat liver mitochondria. A possible explanation for
hyperammonemia in propionic and methylmalonic acidemia. J Clin Invest 64:
1544-1551.
Dahl DR. 1968. Short chain fatty acid inhibition of rat brain Na-K adenosine
triphosphatase. J Neurochem 15:815-20.
D'Alessandro A, Giardina B, Gevi F, Timperio AM, Zolla L. 2012. Clinical Metabolomics:
the next stage of clinical biochemistry. Blood Transfus. 10 Suppl 2: S19-24.
Daniotti M, La Marca G, Fiorini P, Filippi L. 2011. New developments in the treatment of
hyperammonemia: emerging use of carglumic acid. Int J Gen Med. 4: 21–28.
De Sousa C, Chalmers RA, Stacey TE, Tracey BM, Weavers CM, Bradley D. 1986. The
response to L-carnitine and glycine therapy in isovaleric acidaemia. Eur J
Pediatr 144: 451-456.
Dionisi-Vici C, Deodato F, Röschinger W, Rhead W, Wilcken B. 2006. Classical organic
acidurias, propionic aciduria, methylmalonic aciduria and isovaleric aciduria:
Long-term outcome and effects of expanded newborn screening using tandem
mass spectrometry. J Inherit Metab Dis 29: 383-389.
Dipple KM, McCabe EBR. 2000. Modifier genes convert "simple" Mendelian disorders to
complex traits. Mol Genet Metab 71: 43–50.
Dorland L, Duran M, Wadman SK, Niederwieser A, Bruinvis L, Ketting D. 1983.
Isovalerylglucuronide, a new urinary metabolite in isovaleric acidemia.
Identification problems due to rearrangement reactions. Clin Chim Acta 134: 7783.
Dunn
WB,
Ellis
DI.
2005.
Metabolomics:
current
analytical
platforms
and
methodologies". Trends Anal Chem 24: 285-294.
Duran M, Bruinvis L, Ketting D, Wadman SK, Van Pelt BC, Batenburg-Plenter AM.
1982. Isovaleric acidaemia presenting with dwarfism, cataract and congenital
abnormalities. J Inherit Metab Dis 5:125-127.
Duran M, Van Sprang FJ, Drewes JG, Bruinvis L, Ketting D, Wadman SK. 1979. Two
sisters with isovaleric acidaemia, multiple attacks of ketoacidosis and normal
development. Eur J Pediatr 131: 205-211.
35
Chapter 1
Duran M, Baumgartner ER, Suormala TM et al. 1993. Cerebrospinal fluid organic acids
in biotinidase deficiency. J Inherit Metab Dis 16: 513-516.
Ensenauer R, Vockley J, Willard J. et al. 2004. A common mutation is associated with a
mild, potentially asymptomatic phenotype in patients with isovaleric acidemia
diagnosed by newborn screening. Am J Hum Genet 75: 1136-1142.
Erdem E, Cayonu N, Uysalol E, Yildirmak ZY. 2010. Chronic intermittent form of
isovaleric acidemia mimicking diabetic detoacidosis. J Pediatr Endocrinol Metab
23: 503-505.
Fekete K, Decsi T. 2010. Long-chain polyunsaturated fatty acids in inborn errors of
metabolism. Nutrients 2: 965-974.
Fischer AQ, Challa VR, Burton BK, McLean WT. 1981. Cerebellar haemorrhage
complicating isovaleric acidemia: a case report. Neurology. 31:746-748.
Frerman FE, Goodman SI. 1985. Fluorometric assay of acyl-CoA dehydrogenases in
normal and mutant human fibroblasts. Biochem Med 33:38-44.
Garrod AG. 1909. Inborn errors of metabolism. Oxford University Press, Oxford, UK
German JB, Bauman DE, Burrin DG et al. 2004. Metabolomics in the opening decade of
st
the 21 century: building the roads to individualized health. J Nutr 2729-2732.
German JB, Gillies LA, Smilowitz JT, Zivkovic AM, Watkins SM. 2007. Lipidomics and
lipids profiling in metabonomics. Current opinion in lipidomics. 18:66-71.
Gilbert-Barness E, Barness LA. 1999. Isovaleric acidemia with promyelocytic
myeloproliferative syndrome. Pediatr Dev Pathol. 2:286-291.
Giovannini M, Biasucci G, Luotti D, Fiori L, Riva E. 1995. Nutrition in children affected
by inherited metabolic disease. Ann 1st Super Sanità 31: 489-502.
Go VL, Butrum RR, Wong DA. 2003. Diet, nutrition and cancer prevention: the
postgenomic era, J. Nutr. 133: S3830-S3836.
Goodacre R, Broadhurst D, Smilde AK et al. 2007. Proposed minimum reporting
standards for data analysis in metabolomics, Metabolomics 3:231-241.
Goodacre R. 2005. Metabolomics – the way forward. Metabolomics 1:1-2.
Goodacre R. 2010. An overflow of….what else but metabolism. Metabolomics 6:1-2.
Gregersen N. 1981. The specific inhibition of the pyruvate dehydrogenase complex from
pig kidney by propionyl-CoA and isovaleryl-CoA. Biomedical medicine. 26:20-27.
Gregersen N. 2006. Protein misfolding disorders: Pathogenesis and intervention. J
Inherit Metab Dis 29:456-470.
Grieger C, Geistlinger L, Altmaier E et al. 2008. Genetic meets metablomics: A genomewide association study of metabolite profiles in human serum. Plos Genetics 4:112.
Griffith, WJ. 2008. Metabolomics, Metabonomics and Metabolite Profiling, RSC
Publishing, Royal Society of Chemistry, Cambridge, UK pp 1-323
Grünert SC, Wendel U, Linder M et al. 2012 Clinical and neurological outcome in
symptomatic isovaleric acidemia. Orphanet J Rare Dis 7:9.
36
General introduction and outline of thesis
Haas RH, Parikh S, Falk MJ et al. 2008. The in-depth evaluation of suspected
mitochondrial disease. Mol Genet Metab 94:16-37.
Harrigan GG, Bracket DJ, Boros LG. 2005. Medicinal chemistry, metabolic profiling
and drug discovery: a role for metabolic profiling in reverse pharmacology and
chemical genetics. Mini-Rev Med Chem 5: 13-20.
Hertecant JL, Ben-Rebeh I, Marah MA et al. 2012. Clinical and molecular analysis of
isovaleric academia patients in the United Arab Emirates reveals remarkable
phenotypes and four novel mutations in the IVD gene. Eur J Med Genet 55:671676.
HGMD: Human Gene Mutation Database. Available at http://www.hgmd.org (accessed
October 2012).
Hine DG, Hack AM, Goodman SI, Tanaka K, 1986. Stable isotope dilution analysis of
isovalerylglycine in amniotic fluid and urine and its application for the prenatal
diagnosis of isovaleric acidemia. Pediatr Res. 20:222-226.
Hine DG, Tanaka K. 1984. The identification and excretion pattern of isovaleryl
glucoronoid in the urine of patients with isovaleric academia. Pediatr Res
18:508-513.
Ikeda Y, Fenton WA, Tanaka K. 1984. In vitro translation and post-translational
processing of four mitochondrial acyl-CoA dehydrogenases. Fed Proc. 43:2024.
Ikeda Y, Keese SM, Fenton WA, Tanaka T. 1987. Biosynthesis of four rat liver
mitochondrial acyl-CoA dehydrogenases: In vitro synthesis, import into
mitochondria, and processing of their precursors in a cell-free system and in
cultured cells. Arch Biochem Biophys 252: 662-674.
Ikeda Y, Tanaka K. 1983. Purification and characterization of isovaleryl Co-enzyme A
dehydrogenase from rat liver mitochondria. J Biol Chem 258:1077.
Itoh T, Ito T, Ohba S et al. 1996. Effect of carnitine administration on glycine metabolism
in patients with isovaleric acidemia: significance of acetylcarnitine determination
to estimate the proper carnitine dose. J Exp Med 179:101-109.
Kahler SG, Sherwood WG, Woolf D et al. 1994. Pancreatitis in patients with organic
acidemias. J Pediatr 124:239-243.
Kasapkara CS, Ezgu FS, Okur I, Tumer L, Biberoglu G, Hasanoglu A. 2011. Ncarbamylglutamate treatment for acute neonatal hyperammonemia in isovaleric
acidemia. Eur J Pediatr 170: 799-801.
Katajamaa M, Oresic M. 2007.
Data processing for mass spectrometry-based
metabolomics. J Chrom A 1158:318-328.
Kaya N, Colak D. Al-Bakheet et al. 2012. Identification of a novel mutation in a
consanguineous family with isovaleric acidemia. Gene 513: 297-300
Kelleher JF, Yudkoff M, Hutchinson R, August CS, Cohn RM. 1980. The pancytopenia
of isovaleric acidemia. Pediatrics 65:1023-1027.
37
Chapter 1
Knerr I, Weinhold N, Vockley J, Gibson KM. 2012. Advances and challenges in the
treatment of branched-chain amino/keto acid metabolic defects. J Inherit Metab
Dis 35:29-40.
Kraus JP, Matsubara Y, Barton D et al. 1987. Isolation of cDNA clondes coding for rat
isovaleryl-CoA dehydrogenase and assignment of the gene to human
chromosome 15. Genomics 1:264-269.
Krieger I, Tanaka K. 1976. Therapeutic effects of glycine in isovaleric acidemia. Pediatr
Res 10:25-299.
Lai JC, Cooper AJ. 1991. Neurotoxicity of ammonia and fatty acids: differential inhibition
of mitochondrial dehydrogenases by ammonia and fatty acyl coenzyme A
derivatives. Neurochem Res 16:795-803.
Lai JC, Liang BB, Zhai S, Jarvi EJ, Lu DR. 1994. Brain mitochondrial citrate synthase
and glutamate dehydrogenase: differential inhibition by fatty acyl coenzyme A
derivatives. Metab Brain Dis 9:143-152.
Lee HHC, Lee RSY, Lai CK et al. 2010.
A novel duplication at the putative DNA
polymerase alpha arrest site and a founder mutation in Chinese in the IVD gene
underlie isovaleric acidaemia. Hong Kong Med J 16: 219-222.
Lee Y, Lee DH, Vockley J, Kim ND, Lee, YK, Ki C. 2007. Different spectrum of
mutations of isovaleryl-CoA dehydrogenase (IVD) gene in Korean patients with
isovaleric acidemia. Mol Genet Metab 92:71-77.
Lehnert W, Niederhoff H. 1981. 4-Hydroxyisovaleric acid: a new metabolite in isovaleric
acidemia. Eur J Pediatr. 136: 281-283
a
Lehnert W. 1981 . 3-Hydroxyisoheptanoic acid: a new metabolite in isovaleric acidemia.
Clin Chim Acta. 113: 101-103.
b
Lehnert W. 1981 . Excretion of N-isovalerylglutamic acid in isovaleric acidemia. Clin
Chim Acta 116: 249-253.
Lehnert W. 1983. N-Isovalerylalanine and N-isovalerylsarcosine: two new minor
metabolites in isovaleric acidemia. Clin Chim Acta. 134:207-712.
Levy HL, Erickson AM, Lott IT, Kurtz DJ. 1973. Isovaleric acidemia: results of family
study and dietary treatment. Pediatrics 52:83-94.
Lin W, Wang C, Lee C, Lai C, Tsai Y, Tsai F.
2007. Genetic mutation profile of
isovaleric acidemia patients in Taiwan. Mol Genet Metab 90:134-139.
Lindon JC, Nicholson JK, Holmes E. 2007. The Handbook of Metabonomics and
Metabolomics. Elsevier B.V., The Netherlands. pp 1-555.
Loots DT, Erasmus E, Mienie, LJ. 2005. Identification of 19 new metabolites induced by
abnormal amino acid conjugation in isovaleric academia. Clin Chem 51: 15101512.
Loots DT, Mienie LJ, Erasmus E. 2007. Amino-acid depletion induced by abnormal
amino-acid conjugation and protein restriction in isovaleric acidemia. Eur J Clin
Nut 61: 1323-1327.
38
General introduction and outline of thesis
Loots DT. 2009. Abnormal tricarboxylic acid cycle metabolites in isovaleric acidaemia. J
Inherit Metab Dis 32:403-411.
Luís PB, Ruiter JP, IJlst L, Diogo L, Garcia P, de Almeida IT et al. 2012. Inhibition of 3methylcrotonyl-CoA carboxylase explains the increased excretion of 3hydroxyisovaleric acid in valproate-treated patients. J J Inherit Metab Dis 35:
443-449.
Lynen F. 1961. Biosynthesis of saturated fatty acids. Fed Proc 20:941-951.
Ma H, Sorokin A, Mazein A et al. 2007. The Edinburgh human metabolic network
reconstruction and its functional analysis. Mol Syst Biol. 3: 135-146.
Malins DC, Varanasi U, Wekell JC, Tanaka K. 1972. Lipid biosynthesis and increased in
isovaleric acid in plasma. Science, 176: 1357.
Mamas M, Dunn WB, Neyses L, Goodacre R. 2011. The role of metabolites and
metabolomics in clinically applicable biomarkers of rare disease. Arch Toxicol
85:5-17.
Matthews RT, Yang L, Jenkins BG, et al. 1998. Neuroprotective effects of creatine and
cyclocreatine in animal models of Huntington's disease. J Neurosci 18:156-63.
Mayatepek E, Kurczynski TW, Hoppel CL, 1991. Long-term L-carnitine treatment in
isovaleric acidemia. Pediatr Neurol 7:137-40.
McCabe ERB. 2010. Inborn errors of metbolism: the metabolome is our world.
Presidential address for the 11
th
international congress of inborn errors of
metabolism (ICIEM). Mol Gen Metb 100:1-5.
McHugh D. 2011. Clinical validation of cutoff target ranges in newborn screening of
metabolic disorders by tandem mass spectrometry: a worldwide collaborative
project. Genet Med 13:230-254.
McKean MC, Beckmann JD, Frerman FE. 1983. Subunit structure of electron transfer
flavoprotein. J Biol Chem. 258:1866-1870
Meijer AJ, Lamers WH, Chamuleau AFM. 1990. Nitrogen metabolism and ornithine
cycle function. Physiol Rev 70:701-748.
Millington DS, Kodo N, Norwood DL, Roe CR. 1990. Tandem mass spectrometry: a new
method for screening acylcarnitine propfiling with potential for neonatal
screening for inborn errors of metabolism. J Inher Metab Dis 13:321-324.
Millington DS, Roe CR, Maltby DA, Inoue F. 1987. The endogenous catabolism is the
major source of toxic metabolites in isovaleric acidemia. J Pediatric 110:56-60.
Milner JA. 2003. Incorperating basic nutrition science into health interventions for cancer
prevention. J Nutr 133:S3820-S3826.
Mitchell GA, Gauthier N, Lesimple A, Wang SP, Mamer O, Qureshi I. 2008. Hereditary
and acquired diseases of acyl-coenzyme A metabolism. Mol Genet Metab 94:415.
39
Chapter 1
Mohsen AA et al. 1998. Characterization of molecular defects in isovaleryl-CoA
dehydrogenase in patients with isovaleric acidemia. Biochemistry 37:1032510335.
Mohsen AA, Vockley J. 1995. Identification of active site catalytic residue in human
isovaleryl-CoA dehydrogenase. Biochemistry 34:10146-10152.
Naglak M, Salvo R, Madsen K, Dembure P, Elsas L. 1988. The treatment of isovaleric
acidemia with glycine supplementation. Pediatr Res. 24: 9-13.
Nörstrom A, Lewensohn, R. 2010. Metabolomics: Moving to the clinic. J. Neuroimmune
pharmacol 5:4-17.
Ogier de Baulny H, Dionisi-Vici C, Wendel H. 2012. Branched-chain organic acidurias/
acidaemias in: J. Fernandes, J. Saudubray, G. van den Berghe, J.H. Walter
(Eds), Inborn Metabolic Diseases: Diagnosis and Treatment, Springer Medizin
Verlag Heidelberg, Germany. pp 277-295.
Okamura-Ikeda K, Ikeda Y, Tanaka K. 1985. An essential cysteine residue located in
the vicinity of the FAD-binding site in short-chain, medium-chain, and long-chain
acyl-CoA dehydrogenases from rat liver mitochondria. J Biol Chem 260:13381345.
Parimoo B, Tanaka K. 1993. Structural organization of the human isovaleryl-CoA
dehydrogenase gene. Genomics 15:582-590.
Plebani M, Lippi G. 2013. Personalized laboratory medicine: a bridge to the future. Clin
Chem Lab Med 51:703-706.
Qui WJ, Gu XF, Ye J et al. 2008. Clinical and mutational study of a Chinese infant with
isovaleric acidemia. Zhonghua Er Ke Za Zhi 46:526-530.
Reinecke CJ, Koekemoer G, Van der Westhuizen FH et al. 2012. Metabolomics of
urinary organic acids in respiratory chain deficiencies in children. Metabolomics.
8:264-283.
Reinke SN, Broadhurst DI. 2012. Moving metabolomics from data-driven science to an
integrative systems science. Genome medicine 4:1-3.
Rhead WJ, Hall CL, Tanaka K. 1981 Novel tritium release assays for isovaleryl-CoA and
butyryl-CoA dehydrogenase. J. Biol. Chem. 256: 1616-1624.
+
+
Ribeiro CA, Balestro F, Grando V, Wajner M. 2007. Isovaleric acid reduces Na , K ATPase activity in synaptic membranes from cerebral cortex of young rats. Cell
Mol Neurobiol 27:529-540.
Ribeiro CAJ, Leipnitz G, Amaral AU, De Bortoli G, Seminotti B, Wajner M. 2009.
Creatine
administration
prevents
Na+,K+-ATPase
inhibition
induced
by
intracerebroventricular administration of isovaleric acid in cerebral cortex of
young rats. Brain Res 262:81-88.
Robinson M, White FJ, Cleary MA, Wraith E, Lam WK., Walter JH. 2000. Increased risk
of vitamin B12 deficiency in patients with phenylketonuria on an unrestricted or
relaxed diet. J Pediatr 136: 545-547.
40
General introduction and outline of thesis
Roe CR, Millington DS, Maltby DA, Kahler SG, Bohan TP. 1984. L-carnitine therapy in
isovaleric acidemia. J Clin Invest 74:2290-2295.
Sabourin PJ, Bieber LL. 1982. The mechanism of alpha-ketoisocaproate oxygenase.
Formation of beta-hydroxyisovalerate from alpha-ketoisocaproate. J Biol Chem.
257:7468-7471.
Sánchez-Alcudia R, Pérez B, Ugarte M, Desviat LR. 2012. Feasibility of nonsense
mutation readthrough as a novel therapeutical approach in propionic acidemia.
Hum Mutat. 33:973-980.
Scrutton MC. 1974. Pyruvate carboxylase. Studies of activator-independent catalysis
and of the specificity of activation by acyl derivatives of coenzyme A for the
enzyme from rat liver. J Biol Chem. 249:7057-7067.
Shigematsu Y, Hata I, Nakai A et al. 1996. Prenatal diagnosis of organic acidemias
based on amniotic fluid levels of acylcarnitines. Pediatr Res. 39:680-684.
Shih VE, Aubry RH, DeGrande G, Gursky SF, Tanaka K. 1984. Maternal isovaleric
acidemia. 1984. J Pediatr 105:77-78.
Shlomi T, Cabili MN, Ruppin E. 2009. Predicting metabolic biomarkers of human inborn
errors of metabolism. Mol Syst Biol. 5:263
Shotwell MA, Oxender DL. 1983 The regulation of neutral amino acid transport by
amino acid availability in animal cells. Trends Biochem Sci 8:314-316.
Smeitink, J Zeviani M, Turnbull DM, Jacobs H. 2006. Mitochondrial medicine: A
metabolic perspective on the pathology of oxidative phosphorylation disorders.
Cell Metab 3:9-13.
Smilde AK, Jeroen J Jansen JJ, Hoefsloot HCJ, Lamers RAN, van der Greef J,
Timmerman ME. 2005. ANOVA-simultaneous component analysis (ASCA): a
new tool for analyzing designed metabolomics data. Bioinformatics 21:30433048
Smuts I, Van der Westhuizen FH, Louw R, Mienie LJ et al. 2012. Disclosure of a
putative biosigniture for respiratory chain disorder through a metabolomics
approach. Metabolomics. 9:379-391
Solanky KS, Bailey NJ, Beckwith-Hall BM. 2003. Application of biofluid 1H NMR-based
metabonomic techniques for the analysis of the biochemical effects of dietary
isoflavoneson human plasma profile. Anal. Biochem. 323:197-204.
Solano AF, Leipnitz G, De Bortoli GM et al. 2008. Induction of oxidative stress by the
metabolites accumulating in isovaleric acidemia in brain cortex of young rats.
Free Radic Res 42:707-715.
Stanley CA, Hale E, Whiteman DEH, et al. 1983. Systemic carnitine deficiency in
isovaleric acidemia. Pediatr Res 17:296A.
Stewart PM, Walser M. 1980. Failure of the normal ureagenic response to amino acids
in organic acid-loaded rats. Proposed mechanism for the hyperammonemia of
propionic and methylmalonic acidemia. J Clin Invest. 66:484-492.
41
Chapter 1
Stumpf DA, Parker WD Jr, Angelini C, 1985. Carnitine deficiency, organic acidemias,
and Reye's syndrome. Neurology. 35:1041-1045.
Suomalainen A. 2011. Biomarkers for mitochondrial respiratory chain disorders. J.
Inherit Metab Dis. 34:277-282.
Suryawan A, Hawes JW, Harris RA et al. 1998. A metabolic model of human branchedchain amino acid metabolism. Am J Clin Nutr. 98:72-81.
Tanaka K, 1990. Isovaleric acidemia: personal history, clinical survey and study of the
molecular basis. Prog Clin Biol Res 321:273-290.
Tanaka K, Budd MA, Efron ML, Isselbacher KJ. 1966.
Isovaleric acidemia: a new
genetic defect of the leucine metabolism. Proc Natl Acad Sci USA 56: 236-242.
Tanaka K, Ikeda Y, Matsubara Y, Hyman D. 1988. Molecular basis of isovaleric
acidemia and the study of the acyl-CoA dehydrogenase family. Adv Neurol.
48:107-131.
Tanaka K, Isselbacher KJ. 1967. The isolation and identification of N-isovalerylglycine
from urine of patients with isovaleric acidemia. J Biol Chem. 242:2966-2972.
Tanaka K, Orr JC, Isselbacher KJ. 1968. The identification of 3-hydroxyisovaleric acid in
the urine of a patient with isovaleric acidemia. Biochim Biophys Acta 152:638641.
Teague C, Holmes E, Maibaum E et al. 2004. Ethyl glucoside in human urine following
dietary exposure: detection by 1H NMR spectrometry as a result of
metabonomic screening in humans. Analyst. 129:259-264.
Tiffany KA, Robert DL, Wang M et al. 1997. Structure of human isovaleryl-CoA
dehydrogenase at 2,6Å resolution: Structural basis for substrate specificity.
Biochemistry 36:8455-8464.
Truscott RJ, Malegan D, McCairns E et al. 1981. New metabolites in isovaleric
acidemia. Clin Chim Acta. 110:187-203.
Turan N, Katari S, Coutifaris C, Sapienza C. 2010. Explaining inter-individual variability
in phenotype: Is epigenietics up to the challenge. Epigenetics 5:1-4.
Van Batenburg MF, Coulier L, Van Eeuwijk F, Smilde AK, Westerhuis JA. 2011. New
figures of merit for comprehensive functional genomics data: the metabolomics
case. Anal Chem 83: 3267-3274.
Van der Graaf M, Engelke UF, Morava E. 2010. Cerebral accumulation of 3hydroxyisovaleric
acid in adults
until
recently unaware
of
having
3-
Methylcrotonyl-CoA Carboxylase (MCC) deficiency. Proc Intl Soc Mag Reson
Med 18:2128.
Van der Greef J, Smilde AG. 2005. Symbiosis of chemometrics and metabolomics: past,
present, and future. J Chemometrics 19:376-386.
Van Hove JL, Kahler SG, Millington DS et al. 1994. Intravenous L-carnitine and acetylL-carnitine in medium-chain acyl-coenzyme A dehydrogenase deficiency and
isovaleric acidemia. Pediatr Res 35:96-101.
42
General introduction and outline of thesis
Van Kovering M, Nissen SL. 1992. Oidation of leucine and alpha-ketoisocaproate to bhydroxy-b-methylbutyrate in vivo. Am J Physiol Endocrinol Metab. 262:27-30.
Vangala S, Tonelli A. 2007. Biomarkers, metabonomics and drug development: Can
inborn errors of metabolism help in understanding drug toxicity? AAPS Journal
9:E283-E297.
Vatanavicharn N, Liammongkolkul S, Sakamoto O, Sathienkijkanchai A, Wasant P.
2011. Phenotypic and mutation spectrums of Thai patients with isovaleric
acidemia. Pediatr Int. 53:990-994.
Vlaardingerbroek H, Hornstra G, De Koning TJ, Smeitink JA, Bakker MJ, de Klerk HB et
al. 2006. Essential polyunsaturated in plasma end erythrocytes of children with
inborn errors of amino acid metabolism. Mol Genet Metab 88:159-165.
Vockley J, Ensenauer R. 2006 Isovaleric acidemia: New aspects of genetic and
phenotypic heterogeneity. Am J Med Genet Part C 142C:95-103.
Vockley J, Parimoo B, Tanaka K. 1991. Molecular characteristics of four different
classes of mutations in isovaleryl-CoA dehydrogenase gene responsible for
isovaleric acidemia. Am J Hum Genet 49:147-157.
Vockley J, Rogan PK, Anderson BD et al. 2000 Exon skipping in IVD RNA processing in
isovaleric acidemia caused by point mutations in the coding region of the IVD
gene. Am J Hum Genet 66: 356-367.
Vockley J, Zschocke J, Knerr I, Vockley CW, Gibson KM. 2012. Branched chain organic
acidurias in: Valle D, Beaudet A, Vogelstein B, Kinzler KW (Eds.). The Online
Metabolic and Molecular Bases of Inherited Disease, Part 8 McGraw-Hill,
www.ommbid.com (accessed on 2 October 2012).
Wanders RJA, Ruiter JP, IJlst L, Waterham HR, Houten SM. 2010. The enzymology of
mitochondrial fatty acid beta-oxidation and its application to follow-up analysis of
positive neonatal screening results. J Inherit Metab Dis 33: 479-494.
Wang Y, Geer LY, Chappey C, Kans JA, Bryant SH. 2000.Cn3D: Sequence and
structure views for Entrez. Trends Biochem Sci 25:300-302.
Wappner RS, Gibson KM. 2006. Disorders of leucine metabolism in: Physician's guide
to the treatment and follow-up of metabolic diseases. N Blau · GF Hoffmann, J
Leonard, JTR Clarke (Eds.). Springer-Verlag Berlin Heidelberg: Germany pp 5978.
Watkins SM, Hammock BD, Newman JW, German JB. 2001. Individual metabolism
should guide agriculture towards foods for improved health and nutrition. Am J
Clin Nutr 74:283-286.
Weckwerth, W. 2007. Metabolomics: Methods and Protocols, Humana Press inc., New
Jersey, USA. pp 1-286
Wendel U, Eißler A, Sperl W, Schadewaldt P. 1995. On the differences between urinary
metabolite excretion and odd-numbered fatty acid production in propionic and
methylmalonic acidaemias J Inherit Metab Dis18: 584-591.
43
Chapter 1
Whitfield PD, German AJ, Noble PM. 2004. Metabolomics: an emerging post-genomic
tool for nutrition. Brit J Nutr 92:549-555.
Wikoff WR, Gangnoiti JA, Barshop BA, Siuzdak G. 2007. Metabolomics identifies
perturbations in human disorders of propionate metabolism. Clin Chem 53:21692176.
Wilcken B, Wiley V, Hammond J, Carpenter K. 2003. Screening newborns for inborn
errors of metabolism by tandem mass spectrometry. N Engl J Med. 348:23042312.
Woolf SH. 2008. The Meaning of Translational Research and Why It Matters. J Ame
Med Ass 299:211-213.
Worthen HG, Al Ashwal A, Ozand PT et al. 1994. Comparative frequency and severity
of hypoglycemia in selected organic acidemias, branched chain amino acidemia,
and disorders of fructose metabolism. Brain & Development. 16:81-85.
Yudkoff
M, Cohn RM, Puschak R, Rothman R, Segal S. 1978. Glycine therapy in
isovaleric acidemia. J Pediatr 92:813-817.
Zeczycki TN, St. Maurice M, Attwood PV. 2010. Inhibitors of pyruvate carboxylase.
Open Enzym Inhib J. 3:8-26.
Zhang A, Sun H, Wu X, Wang X. 2012. Urine metabolomics. Clin Chim Acta 414:65-69.
44