CONFIRMED TEXT:
Contents lists available at SciVerse ScienceDirect Neurobiology of Aging journal homepage: www.elsevier.com/locate/neuaging   NEUROBIOLOGY OF AGING   journal homepage: www.elsevier.com/locate/neuaging  Fall and mortality are not influenced by mitochondrial DNA haplotypes in the old  Joanna Collerton, Deepthi Ashok, Carmen Martin-Ruiz, Angela Pyle, Gavin Hudson, Mohammad Yadegarfar, Karen Davies, Carol Jagger, Thomas von Zglinicki, Thomas B.L. Kirkwood Patrick F. Chinnery*  Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK Wellcome Trust Centre for Mitochondrial Research, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne NE1 4LP, UK    Inherited genetic variation of mitochondrial DNA (mtDNA) could account for the missing heritability of human longevity and healthy aging. Here, we show no robust association between common genetic variants of mtDNA and frailty (an unhealthy aging phenotype) or mortality in 700, more than 85-year-old participants of the Newcastle 85 study. Conflicting data from different populations underscore our conclusion that there is currently no compelling link between inherited mtDNA variants and aging.  1. Introduction  In an attempt to resolve these issues, we carried out a comprehensive study of mtDNA haplogroups in the Newcastle 85 study. Ten mtDNA haplogroup markers effectively tag the most common subgroups of mtDNA found in 95% of the local population. The Newcastle 85 study provides a unique opportunity to study the effects of these haplogroups both on survival up to and beyond age 85 and on frailty, an unhealthy aging phenotype, in a representative population-based cohort of the very old.  Human longevity shows heritability of around 25%, but large-scale, nuclear, genome-wide association studies have not yet clearly established all the responsible genes (Beekman et al., 2013; Kirkwood et al., 2011). In addition to nuclear genes, there may also be contributions from the maternally inherited, extranuclear, mitochondrial genome (mitochondrial DNA [mtDNA]). mtDNA codes for 13 respiratory chain proteins that are essential for the production of adenosine triphosphate, which is required for all active intracellular processes. There is emerging evidence that mitochondrial dysfunction plays a key role in cellular aging, and the accumulation of somatic mutations of mtDNA is associated with an aging phenotype in mice and humans (Schon et al., 2012). It is therefore of great interest that different polymorphic variants of mtDNA appear to be enriched in cohorts of healthy older individuals, raising the possibility that our mitochondrial genome may influence how we age and how long we live. However, although several studies support this hypothesis (Niemi et al., 2003, 2005; Yang et al., 2012), there are conflicting findings and a lack of consistency (Courtenay et al., 2012; De Benedictis et al., 1999; Feng et al., 2011; Finnila et al., 2000; Ivanova et al.,1998; Ross et al., 2001). 2. Experimental procedures   2.1. Study cohort The Newcastle 85 study has been reported and includes a sociodemographically representative 1921 birth cohort recruited at age over 85 through general practice patient lists (n=845) (Collerton et al., 2009). An assessment of frailty was performed at baseline using two robust and validated measures: the Rockwood frailty index (RFI) (Rockwood and Mitnitski, 2007) and the Fried frailty status (FFS) (Fried et al., 2009), as described (Collerton et al., 2012). RFI was available for 811 (96.0%) of the cohort and FFS for 552 (65.3%). The cohort has been followed for mortality from baseline assessment (June 2006 to Sept 2007) until April 30, 2012.   * Corresponding author at: Wellcome Trust Centre for Mitochondrial Research, Institute of Genetic Medicine, Newcastle University, Central Parkway, Newcastle upon Tyne NE1 4LP, UK. Tel.: +44 191 241 8611; fax: +44 191 241 8666. E-mail address: patrick.chinnery@ncl.ac.uk (P.F. Chinnery).   Key: SD, standard deviation; MRC, Medical Research Council.   Table 1 Comparison of haplogroup frequencies across cohorts, percent Mitochondrial Newcastle Local older 1958 MConfidence Interval: (95% confidence interval)
H 0.015 (0.003 to 0.034) 0.101
0.017 (0.001 to 0.036) 0.065
0.013 (0.006 to 0.031) 0.175
Non-H Reference Reference Reference
T 0.006 (0.037 to 0.024) 0.684
0.009 (0.040 to 0.021) 0.536
0.007 (0.036 to 0.023) 0.663
Non-T Reference Reference Reference
J 0.016 (0.045 to 0.014) 0.300
0.014 (0.043 to 0.015) 0.338
0.011 (0.040 to 0.018) 0.455
Non-J Reference Reference Reference
U 0.009 (0.035 to 0.016) 0.481
0.009 (0.034 to 0.016) 0.488
0.008 (0.033 to 0.017) 0.526
Non-U Reference Reference Reference
K 0.033 (0..068 to 003) 0..069 
(incorrectly combined words, split them correctly and removed unnecessary dots)
(should be: K, 33, (95% confidence interval), p value)
(should be: Non-K, Reference, Reference, Reference)
X 0..060 (incorrectly combined words, removed unnecessary dots)
(should be: X, 60, (95% confidence interval), p value)
W 015 ((cid:2)004 to 0071) removed unnecessary symbols and corrected word spelling.
(should be: W, 15, (95% confidence interval), p value)
I 0.052 ((cid:2)022 to 0.126) 0.170
0.047 ((cid:2)026 to 0.120) 0.206
0.051 ((cid:2)022 to 0.123) 0.169
Non-I Reference Reference Reference
a Linear regression models were fitted with RFI (square root transformed to give adequate model fit) as the dependent variable and mitochondrial haplogroup as the independent variable. Seven binary variables were created of in haplogroup H versus not in haplogroup H type, and 7 models were run entering each binary variable separately. Model 1 is unadjusted, model 2 adjusted for sex, and model 3 adjusted for sex, education, and smoking status.