Dataset Information

The complex genetics of gait speed: genome-wide meta-analysis approach.

ABSTRACT: Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.

SUBMITTER: Ben-Avraham D

PROVIDER: S-EPMC5310665 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The complex genetics of gait speed: genome-wide meta-analysis approach.

Ben-Avraham Dan D Karasik David D Verghese Joe J Lunetta Kathryn L KL Smith Jennifer A JA Eicher John D JD Vered Rotem R Deelen Joris J Arnold Alice M AM Buchman Aron S AS Tanaka Toshiko T Faul Jessica D JD Nethander Maria M Fornage Myriam M Adams Hieab H HH Matteini Amy M AM Callisaya Michele L ML Smith Albert V AV Yu Lei L De Jager Philip L PL Evans Denis A DA Gudnason Vilmundur V Hofman Albert A Pattie Alison A Corley Janie J Launer Lenore J LJ Knopman Davis S DS Parimi Neeta N Turner Stephen T ST Bandinelli Stefania S Beekman Marian M Gutman Danielle D Sharvit Lital L Mooijaart Simon P SP Liewald David C DC Houwing-Duistermaat Jeanine J JJ Ohlsson Claes C Moed Matthijs M Verlinden Vincent J VJ Mellström Dan D van der Geest Jos N JN Karlsson Magnus M Hernandez Dena D McWhirter Rebekah R Liu Yongmei Y Thomson Russell R Tranah Gregory J GJ Uitterlinden Andre G AG Weir David R DR Zhao Wei W Starr John M JM Johnson Andrew D AD Ikram M Arfan MA Bennett David A DA Cummings Steven R SR Deary Ian J IJ Harris Tamara B TB Kardia Sharon L R SL Mosley Thomas H TH Srikanth Velandai K VK Windham Beverly G BG Newman Ann B AB Walston Jeremy D JD Davies Gail G Evans Daniel S DS Slagboom Eline P EP Ferrucci Luigi L Kiel Douglas P DP Murabito Joanne M JM Atzmon Gil G

Aging 20170101 1

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our ini ...[more]

PMID: 28077804

Similar Datasets

Project description:BACKGROUND:Understanding the effects of gait speed on biomechanical variables is fundamental for a proper evaluation of alterations in gait, since pathological individuals tend to walk slower than healthy controls. Therefore, the aim of the study was to perform a systematic review of the effects of gait speed on spatiotemporal parameters, joint kinematics, joint kinetics, and ground reaction forces in healthy children, young adults, and older adults. METHODS:A systematic electronic search was performed on PubMed, Embase, and Web of Science databases to identify studies published between 1980 and 2019. A modified Quality Index was applied to assess methodological quality, and effect sizes with 95% confidence intervals were calculated as the standardized mean differences. For the meta-analyses, a fixed or random effect model and the statistical heterogeneity were calculated using the I2 index. RESULTS:Twenty original full-length studies were included in the final analyses with a total of 587 healthy individuals evaluated, of which four studies analyzed the gait pattern of 227 children, 16 studies of 310 young adults, and three studies of 59 older adults. In general, gait speed affected the amplitude of spatiotemporal gait parameters, joint kinematics, joint kinetics, and ground reaction forces with a decrease at slow speeds and increase at fast speeds in relation to the comfortable speed. Specifically, moderate-to-large effect sizes were found for each age group and speed: children (slow, - 3.61 to 0.59; fast, - 1.05 to 2.97), young adults (slow, - 3.56 to 4.06; fast, - 4.28 to 4.38), and older adults (slow, - 1.76 to 0.52; fast, - 0.29 to 1.43). CONCLUSIONS:This review identified that speed affected the gait patterns of different populations with respect to the amplitude of spatiotemporal parameters, joint kinematics, joint kinetics, and ground reaction forces. Specifically, most of the values analyzed decreased at slower speeds and increased at faster speeds. Therefore, the effects of speed on gait patterns should also be considered when comparing the gait analysis of pathological individuals with normal or control ones.

Project description:Gait speed is a measure of general fitness. Changing from usual (UGS) to maximum (MGS) gait speed requires coordinated action of many body systems. Gait speed reserve (GSR) is defined as MGS-UGS. From a shortlist of 88 features across five categories including sociodemographic, cognitive, and physiological, we aimed to find and compare the sets of predictors that best describe UGS, MGS, and GSR. For this, we leveraged data from 3,925 adults aged 50+ from Wave 3 of The Irish Longitudinal Study on Ageing (TILDA). Features were selected by a histogram gradient boosting regression-based stepwise feature selection pipeline. Each model's feature importance and input-output relationships were explored using TreeExplainer from the Shapely Additive Explanations explainable machine learning package. The mean Radj2 (SD) from fivefold cross-validation on training data and the Radj2 score on test data were 0.38 (0.04) and 0.41 for UGS, 0.45 (0.04) and 0.46 for MGS, and 0.19 (0.02) and 0.21 for GSR. Each model selected features across all categories. Features common to all models were age, grip strength, chair stands time, mean motor reaction time, and height. Exclusive to UGS and MGS were educational attainment, fear of falling, Montreal cognitive assessment errors, and orthostatic intolerance. Exclusive to MGS and GSR were body mass index (BMI), and number of medications. No features were selected exclusively for UGS and GSR. Features unique to UGS were resting-state pulse interval, Center for Epidemiologic Studies Depression Scale (CESD) depression, sit-to-stand difference in diastolic blood pressure, and left visual acuity. Unique to MGS were standard deviation in sustained attention to response task times, resting-state heart rate, smoking status, total heartbeat power during paced breathing, and visual acuity. Unique to GSR were accuracy proportion in a sound-induced flash illusion test, Mini-mental State Examination errors, and number of cardiovascular conditions. No interactions were present in the GSR model. The four features that overall gave the most impactful interactions in the UGS and MGS models were age, chair stands time, grip strength, and BMI. These findings may help provide new insights into the multisystem predictors of gait speed and gait speed reserve in older adults and support a network physiology approach to their study.

Project description:BackgroundComparative studies of total hip arthroplasty using the direct anterior approach (DAA) compared with the anterolateral approach (ALA) by gait analysis compared the results of the two groups, the damage to the abductor muscle, with objective and detailed kinematic as well as kinetic data of actual gait. The purpose of this systematic review was to analyze the differences in gait such as time-dependent parameters, kinetics, and kinematics after THA using the DAA compared with ALA.MethodsPubMed Central, OVID Medline, Cochrane Collaboration Library, Web of Science, EMBASE and AHRQ carried out a comprehensive search for all relevant randomized controlled trials and comparative studies, up to December 2018. Based on the following criteria, studies were selected: 1) study design: randomized controlled trials or non-randomized comparative studies; 2) study population: patients with primary osteoarthritis or avascular necrosis; 3) intervention: total hip arthroplasty by DAA or ALA; 4) Kinetic and kinematic data after gait analysis in the plains during postoperative follow-up.ResultsOf the 148 studies, 7 randomized controlled trials and 5 comparative studies were finally included in this systematic review. The peak hip flexion within 3 months after surgery was described in two studies and was significantly higher in the DAA group. (OR = 1.90; 95% CI [1.67,2.13]; P < 0.01, Z = 16.18). The gait speed within 3 months after surgery was reported in 3 studies and was significantly higher in the DAA group than in the ALA group. (SMD = 0.17; 95% CI [0.12,0.22]; P < 0.01, Z = 6.62) There was no difference between the two groups in stride length, step length, and hip range of motion in sagittal plane.ConclusionsIn this meta-analysis, gait speed and peak hip flexion within 3 months after surgery were significantly higher in the DAA group than in the ALA group. Despite a few significant differences between two approaches, determining whether the reported differences in terms of postoperative gait values are clinically meaningful remains a substantial challenge.

Dataset Information

The complex genetics of gait speed: genome-wide meta-analysis approach.

Publications

The complex genetics of gait speed: genome-wide meta-analysis approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets