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Mitochondrial haplogroups

Mitochondrion 11 (2011) 855861

Contents lists available at ScienceDirect

Mitocho

j ourna l homepage: www.emtDNAOxidative phosphorylation

1. Introduction

The vast majority of the energy needs of the human body are met bymitochondrial oxidative phosphorylation (OXPHOS). OXPHOS takesplace entirely inmitochondria and is a highly efcient systemdependentupon the coordinated expression and interaction of genes encoded inboth the nuclear and mitochondrial genomes. The mtDNA is a circulardouble-stranded DNA molecule of 16.6 kb in humans that encodes 13essential polypeptides of the OXPHOS system and the necessary RNAmachinery for their translation within the mitochondria. MtDNA doesnot recombine, is maternally inherited (Giles et al., 1980), and has aunique organization in that its structural genes lack introns, intergenicspaces, and 5 and 3 noncoding sequences. Each human cell contains

Human mtDNA is highly variable and approximately one-third ofsequence variants found in the general population may be functionallyimportant (Wallace et al., 2010). The genes of the mtDNA are central toenergy production, both to generate ATP and to generate heat tomaintain body temperature. Impaired mitochondrial function resultingfrommitochondrial DNA (mtDNA) and/or nuclear DNAvariation is likelyto contribute to an imbalance in cellular energy homeostasis, increasevulnerability to oxidative stress, and increase the rate of cellularsenescence and aging.

The evolution of humanmtDNA is characterized by the emergenceofdistinct lineages associated with themajor global ethnic groups. Recentanalyses support all modern mtDNA haplogroups being ultimatelytraceable to matrilineal ancestors that lived in Africa approximatelyhundreds ofmitochondria and thousands of cop(mtDNA)with the number of copies being depe

Corresponding author at: California Pacic MedicalFrancisco Coordinating Center, UCSF, 185 Berry StreFrancisco, CA 94107-1728, USA.

E-mail address: gtranah@sfcc-cpmc.edu (G.J. Tranah1 For the Health, Aging and Body Composition Study.

1567-7249/$ see front matter 2011 Elsevier B.V. andoi:10.1016/j.mito.2011.04.005 2011 Elsevier B.V. and Mitochondria Research Society. All rights reserved.EnergeticsMitochondriaProgram in Medical and Population Genetics, B

a r t i c l e i n f o

Article history:Received 1 December 2010Received in revised form 25 March 2011Accepted 29 April 2011Available online 9 May 2011

Keywords:Metabolic rateThe role of climate in driving selection of mtDNA as Homo sapiensmigrated out of Africa into Eurasia remainscontroversial. We evaluated the role of mtDNA variation in resting metabolic rate (RMR) and total energyexpenditure (TEE) among 294 older, community-dwelling African and European American adults from theHealth, Aging and Body Composition Study. Common African haplogroups L0, L2 and L3 had signicantlylower RMRs than European haplogroups H, JT and UK with haplogroup L1 RMR being intermediate to thesegroups. This study links mitochondrial haplogroups with ancestry-associated differences in metabolic rateand energy expenditure.ies ofmitochondrial DNAndent upon the cell type.

Center Research Institute, Sanet, Lobby 4, Suite 5700, San

).

d Mitochondria Research Societi Department of Neurology, Massachusetts Generjal, Boston, MA, 02114, USAitute, 7 Cambridge Center, Cambridge, MA, 02142, USAh Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, 02114al HospitMitochondrial DNA variation in human m

Gregory J. Tranah a,,1, Todd M. Manini b,1, Kurt K. LoAnne B. Newman f,1, Tamara B. Harris g,1, Iva MiljkovSteven R. Cummings a,1, Yongmei Liu e,1

a California Pacic Medical Center Research Institute, San Francisco, CA, 94107, USAb University of Florida, Department of Aging and Geriatric Research, Gainesville, FL, 32601c Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winstod Laboratory of Neurogenetics, Intramural Research Program, National Institute on Aging,e Sticht Center on Aging, Wake Forest University School of Medicine, Winston-Salem, NC,f Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, 15213, USAg Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bey. Atabolic rate and energy expenditure

an c,1, Michael A. Nalls d,1, Stephen Kritchevsky e,1,f,1, Alessandro Bif h,i, j,1,

Alem, NC, 27157, USA, 20892, USA7, USA

a, MD, 20892, USA

ndrion

l sev ie r.com/ locate /mi to150230 thousand years ago (kya) (Soares et al., 2009). MtDNAsequence variation evolved as a result of the sequential accumulationofmutations alongmaternally inherited lineages (Quintana-Murci et al.,1999; Salas et al., 2002). Macrohaplogroup L is specic to sub-SaharanAfricawith themost ancientmtDNAhaplogroups L0 (112188 kya) andL1 (108174 kya) forming the basal lineages of the humanmtDNA treefollowed by L2 (68111 kya) and L3 (5787 kya) (Soares et al., 2009).Haplogroups L0L3 aremost common to sub-Saharan Africa and largely

ll rights reserved.

856 G.J. Tranah et al. / Mitochondrion 11 (2011) 855861of East African origin (Soares et al., 2009), however the widespreaddistribution and diversity of the African haplogroups makes their exactorigin points within Africa difcult to trace with condence (Salas et al.,2002). Dispersal of haplogroup L3 to the Near East ~70 kya, possiblyassociated with an improvement of the climatic conditions after a longperiod of drought (Soares et al., 2009), gave rise to the major Eurasianhaplogroups M and N from which the vast majority of non-Africans aredescended (Salas, Richards, De la Fe, Lareu, Sobrino, Sanchez-Diz,Macaulay and Carracedo, 2002). Haplogroup L3 is more related toEurasian haplogroups than to the most divergent African haplogroupsL1 and L2 (Maca-Meyer, Gonzalez, Larruga, Flores and Cabrera, 2001).Individuals bearing M and N mtDNAs colonized Europe and Asia withthe major European haplogroups (H, V, J, T, U, K, I, W, and X) derivedfrom macrohaplogroup N and the major Asian, Arctic and NativeAmerican haplogroups (A, B, C, D, G, X, Y, and Z) from bothmacrohaplogroups M and N. Europe was rst settled by modernhumans from the near east during the Early Upper Paleolithic ~45 kya(Soares et al., 2009), possibly with the establishment of haplogroup U(4365 kya) (Richards et al., 2000). This rst colonization contributedto ~10% of extant mtDNA lineages (Richards et al., 2000). Modernhumans arriving during the Middle Upper Paleolithic (~2645 kya)and the Late Upper Paleolithic (~915 kya) contributed ~4560% ofextant mtDNA lineages (Richards et al., 2000), including the arrivalof aplogroupsH (1921 kya), J (2227 kya), and T (3340 kya) from theNear East.

It has been proposed that the geographic distribution of mtDNAlineages resulted from selection mainly driven by adaptation toclimate and nutrition (Mishmar et al., 2003; Ruiz-Pesini et al., 2004;Ruiz-Pesini andWallace, 2006; Wallace et al., 2003). According to thishypothesis, certain ancient mtDNA variants permitted humans toadapt to colder climates resulting in the regional enrichment ofspecic lineages. Underlying this selection were functional mtDNAvariants that altered OXPHOS coupling efciency, shifting theenergetic balance from ATP generation to heat production conse-quently allowing Homo sapiens to adapt to colder environments afterleaving Africa (Mishmar et al., 2003; Ruiz-Pesini et al., 2004).

While there is strong evidence supporting selection as an importantfactor in the evolution of humanmtDNA (Balloux et al., 2009; Elson et al.,2004; Kivisild et al., 2006; Marcuello et al., 2009; Martinez-Redondo etal., 2010; Mishmar et al., 2003; Moilanen et al., 2003; Moilanen andMajamaa, 2003; Montiel-Sosa et al., 2006; Ruiz-Pesini et al., 1998; Ruiz-Pesini et al., 2000; Ruiz-Pesini et al., 2004; Ruiz-Pesini and Wallace,2006), not all studies support climate as the driving force for humanmtDNA evolution (Amo and Brand, 2007; Amo et al., 2008; Elson et al.,2004; Kivisild et al., 2006; Moilanen et al., 2003). Evidence that climaticadaptation has inuenced the geographic distribution of mtDNAdiversitywas obtained by examining patterns of genetic variation acrossthe mtDNA coding region, including the 13 mtDNA OXPHOS genes(Balloux et al., 2009; Mishmar et al., 2003; Ruiz-Pesini et al., 2004). Anexamination of regional (tropical, temperate and arctic) gene-specicvariation inmitochondrial OXPHOS genes provided support for adaptiveselection inuencing mtDNA diversity (Mishmar et al., 2003). ATP6washighly variable in themtDNAs from the arctic, cytbwasmore variable intemperate Europe, and COI was highly variable in tropical Africa(Mishmar et al., 2003). These genes were largely invariant in theregions outside of their high adaptation zones (e.g. ATP6 was stronglyconserved in the temperate and tropical zones). These results wereinterpreted as evidence for regional gene-specic selection since thispattern of variationwould not be expected if allmtDNAmutationswererandom and neutral. The frequency of conserved, non-synonymous(missense) mutations across the mtDNA coding region was also foundto increase from tropical Africa to temperate Europe and arcticnortheastern Siberia (Ruiz-Pesini et al., 2004). This excess of non-synonymous mutations in the colder latitudes was interpreted asevidence for adaptive selection playing an important role as people

migrated out of Africa into temperate and arctic Eurasia.Other analyses do not support a simple model in which climaticadaptation has been a major force during human mtDNA evolution(Elson et al., 2004; Kivisild et al., 2006; Moilanen et al., 2003). Forexample, the excess non-synonymous substitutions observed in someOXPHOS genes may not reect positive selection but the relaxation ofnegative selection in specic populations (Elson et al., 2004) or maybe a feature of the terminal branches of the phylogenetic tree,independent of geographical region (Kivisild et al., 2006). Others haveobserved signicant differences in the frequency of non-synonymousmutations among the European haplogroups (Moilanen et al., 2003),suggesting some mutations may be non-neutral within specicphylogenetic lineages but neutral within others.

Functional evidence supporting metabolic differences betweenhaplogroups is equally inconsistent (Amo and Brand, 2007; Amo et al.,2008; Gomez-Duran et al., 2010; Marcuello et al., 2009; Martinez-Redondo et al., 2010;Montiel-Sosa et al., 2006; Ruiz-Pesini et al., 1998;Ruiz-Pesini et al., 2000). Human spermatozoa motility is fullydependent on the functionality of the OXPHOS system and thehaplogroup T samples showed 23% and 29% reductions, respectively,in complexes I and IV activity compared with haplogroup H samples(Ruiz-Pesini et al., 2000). Comparisons of spermatozoa motility amongseveral European haplogroups revealed that sperm from haplogroups Hsubjects swam signicantly faster than those from haplogroups Tsubjects (Ruiz-Pesini et al., 2000). Interestingly, no differences incomplex II activity were observed between haplogroups H and T(complex II is exclusively encodedby thenucleargenome). Spermatozoamotility is directly correlated with activities of OXPHOS complexes IIV(Ruiz-Pesini et al., 1998). Within the broadly distributed Europeanhaplogroup U, sublineages of the group exhibited differences in spermmotility (Montiel-Sosa et al., 2006). Results froma comparisonof cybridscontaining haplogroups H and Uk (Gomez-Duran et al., 2010) suggestthat there are differences in mtDNA and mtRNA levels, mitochondrialprotein synthesis, cytochrome oxidase activity and amount, normalizedoxygen consumption, mitochondrial inner membrane potential andgrowth capacity. Differences in endogenous, leaking and uncoupledrespiration, however, were not observed in comparisons of haplogroupsHandT (Amoet al., 2008) or haplogroupsH andUk (Gomez-Duran et al.,2010).

Conserved cytb mutations were enriched in northern Europe andless prevalent in southern Europe, which is suggestive of selectionallowing adaptation to a colder northern climate (Montiel-Sosa et al.,2006). Maximal oxygen uptake (VO2 max) and mitochondrialoxidative damage have been shown to be higher in human subjectsfrom European haplogroup H compared with haplogroup J (Marcuelloet al., 2009; Martinez-Redondo et al., 2010). By contrast, studies ofcytoplasmic hybrids (cybrids) harboring mitochondria with eitherhaplogroup H or haplogroup T in cultured cells with identical nuclearbackgrounds showno functionally important differences in bioenergeticcapacities and coupling efciencies (Amo et al., 2008) and results weresimilar for both isolated mitochondria and mitochondria within cells.Furthermore, cybrid studies comparing arctic (A, C andD) or tropical (L1,L2 andL3)haplogroupsyieldednooverall differences betweenarctic andtropical mtDNA haplogroups with regard to the overall kinetics ofsubstrate oxidation (Amo and Brand, 2007). Intriguingly, mitochondriafrom Arctic haplogroups had similar or greater coupling efciency thanmitochondria from tropical haplogroups, which is contrary to thehypothesis that mitochondrial haplogroups with lower couplingefciency were positively selected during radiations of modern humans(Amo and Brand, 2007).

To date, the relationship between mitochondrial genetic variationandmetabolic rate has not beendirectly evaluated in human subjects. Inthis study we examined data gathered in the Health, Aging and BodyComposition (Health ABC) Study, a longitudinal study of community-dwelling African and European American adults. We compare restingmetabolic rate (RMR)measuredby indirect calorimetry and total energy

expenditure (TEE) measured by the doubly-labeled water method

857G.J. Tranah et al. / Mitochondrion 11 (2011) 855861across the major African and European haplogroups and identifyindividual mtDNA variants that inuence RMR and TEE. Both activityenergy expenditure and physical activity level decrease with age (Blacket al., 1996; Elia et al., 2000) and are considered to underlie a range ofage-associated pathological conditions, including CVD, neuromuscularand neurological impairments and other life-style changes generallyassociated with senescence (Linnane, 1992). Higher levels of physicalactivity are also associated with reductions in coronary heart disease(Wannamethee et al., 1998), cancer incidence (Gregg et al., 2003), falls(Gregg et al., 2000), and physical disability (Ferrucci et al., 1999).Identifying genetic variants that inuence metabolic rate and energyexpenditure may have broad implications for investigations of func-tional decline and disease risk.

2. Materials and methods

2.1. Participants

Participants were part of the Health, Aging and Body Composition(Health ABC) Study, a prospective cohort study of 3075 community-dwelling black and white men and women living in Memphis, TN, orPittsburgh, PA, and aged 7079 years at recruitment in 1997. To identifypotential participants, a randomsampleofwhite andall blackMedicare-eligible elders, within designated zip code areas, were contacted. To beeligible, participants had to report no difculty with activities of dailyliving, walking a quarter of a mile, or climbing 10 steps without resting.They alsohad tobe free of life-threatening cancerdiagnoses andhavenoplans to move out of the study area for at least 3 years. The sample wasapproximately balanced for sex (51% women) and 42% of participantswere black. Participants self-designated race/ethnicity from a xed setof options (Asian/Pacic Islander, black/African American, white/Caucasian, Latino/Hispanic, do not know, other). The study wasdesigned to have sufcient numbers of Blacks to allow separateestimates of the relationship of body composition to functional decline.All eligible participants signed awritten informed consent, approved bythe institutional review boards at the clinical sites. This study wasapproved by the institutional review boards of the clinical sites and thecoordinating center (University of California, San Francisco).

2.2. Resting metabolic rate

Resting metabolic rate was measured via indirect calorimetry on aDeltatrac II respiratory gas analyzer (Datex Ohmeda Inc, Helsinki),detailed procedures have been described elsewhere (Blanc et al., 2004).While in a fasting state and after 30 min of rest, a respiratory gasexchange hood was placed over the participant's head and RMR wasmeasuredminute-by-minute for 40 min. To avoid gas exchange createdby the initial placement of the hood, only the nal 30 min were used insubsequent calculations. Movement or sleeping during the test wasnoted and those time periods were excluded from the RMR calculation.Methanol burn tests were performed in duplicate once or twice permonth. Carbondioxide recovery averaged100.11.4%at the Pittsburghsite and 100.51.5% at the Memphis site. The gas exchange ratios formethanol differed by 2.5% between sites (Memphis: 0.660.01,Pittsburgh: 0.680.01, pb0.001) and this difference did not demon-strate a trend over time. Therefore, a correction factor was employed toequate the two study sites by dividing the respiratory ratios forparticipants enrolled at Pittsburgh by 1.025.

2.3. Total energy expenditure

Total energy expenditure was measured using the 2-point doubly-labeled water (DLW) technique that has been previously described indetail (Blanc et al., 2002). Briey, on the rst visit, participants ingested2 g/kg estimated total body water (TBW) dose of DLW, composed of

181.9 g/kg estimated TBW of 10% H2 O and 0.12 g/kg estimated TBW of99.9% 2H2O. After dosing, urine sampleswere obtained at approximately2, 3, and 4 h. Two consecutive urine voids were taken during a secondvisit to the laboratory, approximately fourteen days after the rst visit.Plasma from a 5 mL blood sample was obtained from everyone but onlyused for those who had evidence of delayed isotopic equilibration likelycaused from urine retention in the bladder (n=28) (Blanc et al., 2002).Urine and plasma samples were stored at 20 C until analysis byisotope ratio mass spectrometry.

Dilution spaces for 2H and 18O were calculated according to Coward(1990). Total body water was calculated as the average of the dilutionsspaces of 2H and 18O after correction for isotopic exchange (1.041 for 2Hand 1.007 for 18O). Carbon dioxide production was calculated using thetwo-point DLWmethod outlined by Schoeller and colleagues (Schoelleret al., 1986; Schoeller and van Santen, 1982) and TEE was derived usingWeir's equation (Weir, 1949). A food quotient of 0.86was used from thethird National Health and Nutrition Examination Survey (Kant, 2002)and from Black et al. (1986). All values of energy expenditure wereconverted to kilocalories per day (kcal/day) and the thermic effect ofmeals was assumed to be 10% of TEE (Bloesch et al., 1988). Formeasurement of total body water, the intra-subject repeatabilitycalculated as the average percentage difference between the twoanalyses,was0.11.2%. The intra-tester repeatability of TEEbasedonblinded, repeat, urine isotopic analysis was excellent (mean differ-ence=1.25.4%, n=16) and compared well with a recent reviewarticle (Elia et al., 2000).

2.4. Body composition

Lean mass (FFM) was measured annually using a Hologic 4500AScanner (Hologic Inc, Watham, MA). Body composition analysis wasperformed using HOLOGIC software (version 8.21; Hologic Inc).Calibration was performed 3 times per week using whole bodyquality control phantoms outlined in the Hologic manual. Absolutevariation between the clinic sites was monitored by cross-calibratingthe two scanners using separate phantoms. Validation analyses on thescanners detected a systematic overestimation of FFM that wassubsequently corrected by multiplying by a factor of 0.964 (Tylavskyet al., 2003). Values of lean mass were calculated after removing massdue to bone mineral content (BMC).

2.5. Genotyping

Genomic DNA was extracted from buffy coat collected usingPUREGENE DNA Purication Kit during the baseline exam. Genotyp-ing was performed by the Center for Inherited Disease Research(CIDR) using the Illumina Human1M-Duo BeadChip system. Thisplatform includes 138 common mtDNA SNPs with 1% frequencyincluding the majority of haplogroup-dening variants (Saxena et al.,2006). Samples were excluded from the dataset for the reasons ofsample failure, genotypic sexmismatch, and rst-degree relative of anincluded individual based on genotype data. Genotyping of 138mtDNA SNPs (including 137 variant sites) was successful for 2797unrelated individuals including 294 participants with RMR and TEEmeasurements who this analysis is based upon. The major African (L:L0, L1, L2, L3) and European (N: H, JT, UK) haplogroups were denedusing PhyloTree (van Oven and Kayser, 2009) (Table S1).

2.6. Data analysis

Baseline comparisons were performed between African (L) andEuropean (N) haplogroups using analysis of variance (ANOVA) forcontinuous variables and the 2 statistic for categorical variables.Pairwise ANOVA comparisons of RMR and TEE were performed for themajor African (L: L0, L1, L2, L3) and European (N: H, JT, UK)haplogroups using PROC GLM in SAS adjusting for age, sex and lean

mass. Individual mtDNA variants were also examined for associations

with RMR and TEE. To account for confounding by ancestry we derivedeigenvectors using principal components analysis (PCA) for all HealthABC participants with mtDNA genotype data (Bif et al., 2010). Sincemissing genotypes can eliminate individual samples from PCA, webased PCA on coding region variants (mt750 to mt15930) and variantsmissing in b1% of the sample. A total of 107 mtDNA variants generatedeigenvectors for 2471 Health ABC samples. The rst 6 eigenvectorsaccount for 71% of the variance in the dataset. Analyses of individualmtDNA variants were adjusted for age, study site, sex, lean mass, andthe rst 6 eigenvectors of mitochondrial genetic ancestry derived fromprincipal component analysis. All analyses were carried out using SASversion 9.1 (SAS Institute Inc, Cary, NC).

3. Results

Mito9093G (ATP6, complex V) andMito11377A (ND4, complex I) hada RMR of 1647 kcal/day compared with Mito9093A and Mito11377Gcarriers (n=293) having a RMR of 12848 kcal/day. Variants in mt-RNR2, COI, ND5 and CYTB were associated with TEE after multivariateadjustment (Table S3). We examined individual mtDNA variantscontrolling for mtDNA population stratication using mitochondrialPCA (Bif et al., 2010). This method has been demonstrated tooutperform haplogroup-stratied or adjusted association analyseswith no loss in power for detection of true associations (Bif et al.,2010). Additionally, correlation between nuclear and mitochondrial

observed in this study.

Table 2Comparison of resting metabolic rate and total energy expenditure between the majorAfrican and European haplogroups. Values are Least Squares means and Standard Errorsadjusted for age, sex, clinic site and lean mass.

African European

Haplogroup L NN 132 162 P-valueRMR kcal/day, Mean (SE)* 1221 (11) 1326 (9) b0.0001TEE kcal/day, Mean (SE)* 2079 (27) 2237 (25) b0.0001

RMR = Resting metabolic rate determined by indirect calorimetry.TEE = Total energy expenditure determined using doubly-labeled water.

Fig. 1. Summary of resting metabolic rate (kcal/day) for major mitochondrial

858 G.J. Tranah et al. / Mitochondrion 11 (2011) 855861A total of 294 participants with RMR and TEE measurements weregenotyped for 137 variant mtDNA SNPs. We identied 132 partici-pants from African haplogroup L and 162 participants from Europeanhaplogroup N. Descriptive characteristics of haplogroups L and N arelisted in Table 1. Participants from haplogroups L and N had similarage, sex composition, and lean mass. Haplogroup N had an elevatednumber of participants from Pittsburgh than haplogroup L (p=0.03).RMR did not differ between participants from the two clinic sites(p=0.48) but TEE was signicantly higher (p=0.008) amongparticipants from Pittsburgh (221727 kcal/day) when comparedwith those from Memphis (212025 kcal/day) after adjustment forbaseline age, sex, haplogroup, and lean mass. Both RMR and TEE weresignicantly elevated in haplogroup N participants compared tohaplogroup L participants after adjustment for baseline age, sex, clinicsite, and lean mass (Table 2).

Figs. 1 and 2 illustrate the differences in RMR and TEE for thecommonAfrican and European in haplogroups after adjustment for age,sex, clinic site, and lean mass. Haplogroups were ranked in order ofincreasing RMR (Fig. 1) and TEE (Fig. 2) to allow visual comparisons.African haplogroups L0 (n=12), L2 (n=42), and L3 (n=49) hadsignicantly lower RMRs than the three European haplogroups, UK(n=31), JT (n=30), and H (n=70). African haplogroup L1 (n=27)had an RMR intermediate to the European and remaining Africanhaplogroups. For African haplogroup L1, RMR was signicantly lower(p=0.01) than the highest RMR from European haplogroup H andsignicantly higher (p=0.03) than the lowest RMR from Africanhaplogroup L3 (Table 3). African haplogroup L3 had a signicantlylower TEE than the three European haplogroups and haplogroup L2 hada signicantly lower TEE than haplogroups H and JT (Table 4).

Individual mtDNA variants for associations were examined forassociations with RMR and TEE (Tables S2S3). After adjustment forage, sex, lean mass, and 6 eigenvectors of mitochondrial geneticancestry, variants in mt-RNR2, and ND5 were associated with RMR(Table S2). In addition, one participant carrying mtDNA variants

Table 1Baseline characteristics of participants stratied by the major African and Europeanhaplogroups.

African European

Haplogroup L NN 132 162 p-valueAge, years, mean (SD) 73 (2.9) 74 (2.8) 0.12

SexFemale, n (%) 64 (44) 81 (56) 0.29Male, n (%) 68 (46) 64 (48) 0.16

Study siteMemphis, n (%) 78 (49) 82 (51) 0.75Pittsburgh, n (%) 54 (40) 80 (60) 0.03

Lean mass, kg, mean (SD) 48.7 (9.6) 46.6 (10) 0.07Thegreatest differences inRMRandTEEwere observedwhenAfricanhaplogroup L participants were compared to European haplogroup Nprincipal components was limited and adjustment for nuclear PCs hadno effect on mitochondrial analysis (Bif et al., 2010).

4. Discussion

There has been a long-standing debate over the role of climate indriving adaptive selection of mtDNA as Homo sapiensmigrated out ofAfrica into temperate and arctic Eurasia. In this study we observedsignicant bioenergetic differences between the major African andEuropeanmitochondrial haplogroups and among the common Africanhaplogroups. A specic mechanism remains to be identied but thedifferences could be due to effects on respiratory rates, specic dietarymake-up, mitochondrial coupling efciencies, or ATP supply. Someprevious cybrid studies do not support a role for selection of lowerOXPHOS coupling efciencies during radiations of modern humans(Amo and Brand, 2007; Amo et al., 2008), suggesting that more subtlemechanisms may ultimately be responsible for the differenceshaplogroups. Values are LS means and SEs adjusted for age, sex, and lean mass.

859G.J. Tranah et al. / Mitochondrion 11 (2011) 855861participants. Both RMR and TEE were signicantly elevated inhaplogroup N participants compared to those from haplogroup L afteradjustment for baseline age, sex, clinic site, and lean mass. Determiningwhichvariants, genes or OXPHOS complexes contribute to themetabolicdifferences observed between haplogroups L and N will be complicatedby the fact that variants in complexes I (ND3,ND4), III (CytB), IV (COIII)and V (ATP6) all dene this split (van Oven and Kayser, 2009).

Within African haplogroup L, we observed that haplogroup L1 hadan RMR intermediate to the European and remaining Africanhaplogroups. African haplogroups L2 and L3 exhibited signicantlylower RMR values than all others examined. Determining whichvariants or genes contribute to the metabolic differences observed forhaplogroups L1, L2, and L3 may be less difcult since variants inOXPHOS complexes I (ND1, ND3, ND5, and ND6) and IV(COI and COIII)dene these haplogroups (van Oven and Kayser, 2009). Generally,haplogroups L0L3 are most common to sub-Saharan Africa andlargely of East African origin (Soares et al., 2009) but the widespreaddistribution and diversity of these haplogroups makes their exactpoints of origin within Africa difcult to trace (Salas et al., 2002).Approximately 90% of the AfricanAmerican mtDNA pool originatesfrom West and Southwest Africa (Salas et al., 2005). An examination

Fig. 2. Summary of total energy expenditure (kcal/day) for major mitochondrialhaplogroups. Values are LS means and SEs adjusted for age, sex, and lean mass.of the African mtDNA sub-haplogroups that are prominent in AfricanAmericans reveals that haplogroup L1 possibly has a different point oforigin than haplogroups L2 and L3 (Salas et al., 2005), which may inpart contribute to the RMR differences observed between thesegroups. The two L1 sub-haplogroups found in AfricanAmericans, L1band L1c, have a likely origin in the Congo River region of Central Africawhich today includes the equatorial forests (Salas et al., 2005). The L2and L3 sub-haplogroups common in AfricanAmericans, L2a, L2b, L2c,L3b, L3d, and L3e, likely originated in the Niger River region ofWestern African near the Sahara Desert (Salas et al., 2005). It is notclear whether adaptation to different regions played a role in thedevelopment of West African sub-haplogroups of L1, L2, and L3

Table 3Summary of pairwise ANOVA comparisons (p-values) for differences in restingmetabolic rate (kcal/day). Values are Least Squares means and Standard Errorsadjusted for age, sex, and lean mass.

L1 JT UK H

L3 0.03 0.0003 b0.0001 b0.0001L2 ns 0.001 0.0001 b0.0001L0 ns 0.04 0.01 0.002L1 ns ns ns 0.01leading to differences in RMR observed in this study. Of interest,though, is that we have documented RMR differences among WestAfrican sub-haplogroups (L1 vs. L2L3) that had independent originsfrom isolated geographic regions.

The observed haplogroup differences in TEE were not as apparentas those for RMR. The discrepancy between TEE and RMR is largelyattributable to the addition of physical activity as part of TEE. TEE iscomprised of three major components including: RMR; activityenergy expenditure; and the thermic effect of food metabolismManini (2010). RMR accounts for 6080% of TEE, thermic effect offood metabolism uses 10% of TEE, and activity energy expenditure cancomprise 2040% of TEE Manini (2010). RMR is an innate feature of thetissue and the cells that make up that tissue. It is far less determined byenvironmental factors leading to a clearer distinction among hap-logroups. The assessment TEE, however, includes 2040% of energy thatis due to environmental factors outside the control of haplogroupcategorization. By adding a large environmentally determined factor, thehaplogroupdifferences generally become less distinct. Differences in TEEamong European haplogroup N members emerged for TEE, however,with haplogroup JT exhibiting a nominally higher TEE than all otherhaplogroups examined in this study. Haplogroup JT is of Levantineorigins (4254 kya) including present-day Israel, Jordan, Lebanon,Palestine, Syria and the Sinai Peninsula (Richards et al., 2000). Theoriginal peoples associated with haplogroup JT brought farming andherding to Europe beginning about 10 kya. This contrasts with all otherWest Eurasian-origin groups (H, V, U, K, I, W, X) which were largelyhuntergatherers. As with the West African sub-haplogroups, it is notclear whether local adaptation played a role in the development ofhaplogroup JT. Haplogroup J is over-represented in long-lived peopleand centenarians from several populations (De Benedictis et al., 1999;Niemi et al., 2003; Ross et al., 2001). The mtDNA control region variantthat denes Caucasian haplogroup J (mtDNA 295C/T) has been found tochange mitochondrial transcription and copy number (Suissa et al.,2009). Cybrids containinghaplogroup JmtDNAhad a greater than2-foldincrease in mtDNA copy number compared with cybrids containinghaplogroup H mtDNA. This is one of the few examples demonstratingfunctional consequences for a polymorphism underlying a specichaplogroup. In this case, the impact of the haplogroup J regulatory regionmutation on mtDNA replication or stability may partially account forpopulation-based observations that haplogroup J is associated withhuman longevity.

Although functional analyses of the polymorphisms underlyinghaplogroup denitions are needed, there are few reports that identifyfunctional effects of mtDNA polymorphisms mainly due to method-ological difculties (Kazuno et al., 2006). MtDNAs harboring the twofounder macrohaplogroup N missense mutations, ND3 (complex I)nucleotide 10398A/G and ATP6 (complex V) nucleotide 8701A/G,

Table 4Summary of pairwise ANOVA comparisons (p-values) for differences in total energyexpenditure (kcal/day). Values are Least Squares means and Standard Errors adjustedfor age, sex, and lean mass.

UK H JT

L3 0.01 0.0004 0.004L2 ns 0.01 0.02exhibited alterations in mitochondrial matrix pH and intracellularcalcium dynamics (Kazuno et al., 2006). A second study of commonAsian haplogroups identied distinctive intracellular calcium dynamicsamong subhaplogroups G3/G4 and D4a (Kazuno et al., 2008).Subhaplogroup G3/G4 (characterized by mtDNA polymorphisms atsites 1413, 2109, 3434, 5460, 7521, 9011, 9670 and 15940) showedlower cytosolic and mitochondrial calcium levels (Kazuno et al., 2008).By contrast, subhaplogroup D4a (characterized by mtDNA variant13651A/G) showed higher mitochondrial and cytosolic calcium levels(Kazuno et al., 2008). Haplogroup studies can mask the effects of

Gomez-Duran, A., Pacheu-Grau, D., Lopez-Gallardo, E., Diez-Sanchez, C., Montoya, J.,Lopez-Perez, M.J., Ruiz-Pesini, E., 2010. Unmasking the causes of multifactorial

860 G.J. Tranah et al. / Mitochondrion 11 (2011) 855861individual nucleotide changes becausemostmitochondrial haplogroupscan be dened by several control-region and/or coding-region variants.For example, the large number of variants that are closely associatedwith one another and that denemacrohaplogroup N (characterized bymtDNA variants 8701, 9540, 10398, 10873, and 15301 (van Oven andKayser, 2009)) complicate interpretation of the functional and associ-ation data. This implies that functional studies should account for allmtDNA variants within the mitochondrial genome, especially forhaplogroups that can be dened by several variants. The analysis ofmtDNA is further complicatedby recurrentmutation at the samemtDNAsite across divergent haplogroups, especially in the control region,whichcan sometimes erase diagnostic specicity of a particular variant. Thatthe samemutations have been observed repeatedly on differentmtDNAbackgrounds (e.g. haplogroups) has been cited as evidence of conver-gent adaptive evolution of particularmtDNAmutations (Wallace, 2010).

Determining how specic mitochondrial variants inuence physiol-ogy is not only complicated by the complexities of mtDNA evolution asoutlinedabove, but also requires thecoordinatedexpressionofhundredsof nuclear genes and a few dozen mitochondrial genes. This complexgenetic architecture suggests that there might be a complex set of geneinteractions (epistases) involving genetic variation in the nuclear andmitochondrial genomes (Mishmar et al., 2006; Pravenec et al., 2007;Rand et al., 2001; Rand et al., 2006; Rand et al., 2004; Rand and Kann,1998; Willett and Burton, 2003). This is especially important foradmixed populations (e.g. AfricanAmericans and Latinos) where it isnot uncommon to nd individuals with mtDNA and nuclear DNA ofdifferent ancestries (e.g. individuals with African mtDNA in a Europeangenetic background or Native American mtDNA in an African geneticbackground). It is not known how breaking up potentially coadaptedmitochondrial and nuclear OXPHOS gene complexes affects humanhealth, but increasing our understanding of mitochondrialnuclearepistasis in admixed populations may be important for examining thegenetic basis of chronic disease. Because mitochondria play a centralrole in energy metabolism it is likely that mitochondrialnuclearepistasis has important tness effects (Dowling et al., 2007; Hutterand Rand, 1995; Rand et al., 2001; Rawson and Burton, 2002; Rhode andCruzan, 2005; Schmidt et al., 2001; Tranah, 2011; Willett and Burton,2003) and is evolutionarily important (Rand et al., 2004). Both activityenergy expenditure and physical activity level decrease with age(Black et al., 1996; Elia et al., 2000) and are considered to underliea range of age-associated pathological conditions (Gregg et al.,2003; Gregg et al., 2000; Linnane, 1992; Wannamethee et al., 1998).TEE demonstrates an inverted U pattern across the lifespan. In the rsttwo decades of life, TEE increases 2-fold and declines dramatically afterthe age of 40 years (Manini, 2010). Aging is also associated with aprogressive decline in whole-body RMR at a rate of 12% per decadeafter 20 years of age (Elia et al., 2000). Conditions such as Alzheimer's,chronic obstructive pulmonary disease, congestive heart failure,Parkinson's, diabetes, malnourishment and cancer are associated witha change in RMR (Toth and Poehlman, 2000). It is not clear, however,why bioenergetic decline occurs and how increased energetic expendi-ture protects older adults from physical disability and prematuremortality. Future studies seeking to linkmitochondrial genetic variationto bioenergetics, physiological traits or disease risk will need to addressthe analytic challenges posed both by the unique mode of mtDNAevolution and the complexities of examining mitochondrialnuclearepistasis. Identifying mitochondrial genetic variants that inuenceenergy expenditure and metabolic rate could lead to interventions thathave a very signicant impact on prolonging the productive and healthyyears of human life.

Supplementarymaterials related to this article can be found onlineat doi:10.1016/j.mito.2011.04.005.

Conict of interest statementThe authors declare no conict of interest.disorders: OXPHOS differences between mitochondrial haplogroups. Hum. Mol.Genet. 19, 33433353.

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Kant, A.K., 2002. Nature of dietary reporting by adults in the third National Health andNutrition Examination Survey, 19881994. J. Am. Coll. Nutr. 21, 315327.

Kazuno, A.A., Munakata, K., Nagai, T., Shimozono, S., Tanaka, M., Yoneda, M., Kato, N.,Miyawaki, A., Kato, T., 2006. Identication of mitochondrial DNA polymorphisms thatAcknowledgments

This research is supported in part by the Intramural ResearchProgram of the NIH, National Institute on Aging. This research wassupported by NIA contracts N01AG62101, N01AG62103, N01AG62106and NIA grant 1R03AG032498-01. The genome-wide association studywas funded by NIA grant 1R01AG032098-01A1 to Wake ForestUniversity Health Sciences and genotyping services were provided bythe Center for Inherited Disease Research (CIDR). CIDR is fully fundedthrough a federal contract from the National Institutes of Health to TheJohns Hopkins University, contract number HHSN268200782096C.

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Mitochondrial DNA variation in human metabolic rate and energy expenditure1. Introduction2. Materials and methods2.1. Participants2.2. Resting metabolic rate2.3. Total energy expenditure2.4. Body composition2.5. Genotyping2.6. Data analysis

3. Results4. DiscussionConflict of interest statementAcknowledgmentsReferences