On asymptotic distributions of several test statistics for familial relatedness in linear mixed models.

In this study, the asymptotic distributions of the likelihood ratio test (LRT), the restricted likelihood ratio test (RLRT), the F and the sequence kernel association test (SKAT) statistics for testing an additive effect of the expected familial relatedness (FR) in a linear mixed model are examined based on an eigenvalue approach. First, the covariance structure for modeling the FR effect in a LMM is presented. Then, the multiplicity of eigenvalues for the log-likelihood and restricted log-likelihood is established under a replicate family setting and extended to a more general replicate family setting (GRFS) as well. After that, the asymptotic null distributions of LRT, RLRT, F and SKAT statistics under GRFS are derived. The asymptotic null distribution of SKAT for testing genetic rare variants is also constructed. In addition, a simple formula for sample size calculation is provided based on the restricted maximum likelihood estimate of the effect size for the expected FR. Finally, a power comparison of these test statistics on hypothesis test of the expected FR effect is made via simulation. The four test statistics are also applied to a data set from the UK Biobank.

Evaluation of the Genetic Diversity, Population Structure and Selection Signatures of Three Native Chinese Pig Populations.

Indigenous pig populations in Hainan Province live in tropical climate conditions and a relatively closed geographical environment, which has contributed to the formation of some excellent characteristics, such as heat tolerance, strong disease resistance and excellent meat quality. Over the past few decades, the number of these pig populations has decreased sharply, largely due to a decrease in growth rate and poor lean meat percentage. For effective conservation of these genetic resources (such as heat tolerance, meat quality and disease resistance), the whole-genome sequencing data of 78 individuals from 3 native Chinese pig populations, including Wuzhishan (WZS), Tunchang (TC) and Dingan (DA), were obtained using a 150 bp paired-end platform, and 25 individuals from two foreign breeds, including Landrace (LR) and Large White (LW), were downloaded from a public database. A total of 28,384,282 SNPs were identified, of which 27,134,233 SNPs were identified in native Chinese pig populations. Both genetic diversity statistics and linkage disequilibrium (LD) analysis indicated that indigenous pig populations displayed high genetic diversity. The result of population structure implied the uniqueness of each native Chinese pig population. The selection signatures were detected between indigenous pig populations and foreign breeds by using the population differentiation index (FST) method. A total of 359 candidate genes were identified, and some genes may affect characteristics such as immunity (IL-2, IL-21 and ZFYVE16), adaptability (APBA1), reproduction (FGF2, RNF17, ADAD1 and HIPK4), meat quality (ABCA1, ADIG, TLE4 and IRX5), and heat tolerance (VPS13A, HSPA4). Overall, the findings of this study will provide some valuable insights for the future breeding, conservation and utilization of these three Chinese indigenous pig populations.

HSSG: Identification of Cancer Subtypes Based on Heterogeneity Score of A Single Gene.

Cancer is a highly heterogeneous disease, which leads to the fact that even the same cancer can be further classified into different subtypes according to its pathology. With the multi-omics data widely used in cancer subtypes identification, effective feature selection is essential for accurately identifying cancer subtypes. However, the feature selection in the existing cancer subtypes identification methods has the problem that the most helpful features cannot be selected from a biomolecular perspective, and the relationship between the selected features cannot be reflected. To solve this problem, we propose a method for feature selection to identify cancer subtypes based on the heterogeneity score of a single gene: HSSG. In the proposed method, the sample-similarity network of a single gene is constructed, and pseudo-F statistics calculates the heterogeneity score for cancer subtypes identification of each gene. Finally, we construct gene-gene networks using genes with higher heterogeneity scores and mine essential genes from the networks. From the seven TCGA data sets for three experiments, including cancer subtypes identification in single-omics data, the performance in feature selection of multi-omics data, and the effectiveness and stability of the selected features, HSSG achieves good performance in all. This indicates that HSSG can effectively select features for subtypes identification.

A new strategy based on PCA for inter-batches quality consistency evaluation.

Due to cultivation position, climate, harvest times, storage conditions and processing method, the evaluation of intra- and inter- batches quality consistency of botanical drugs has always been a thorny problem since it concerns safety and efficacy. The combination of fingerprint based on instrumental analysis and chemometrics is a common evaluation method in recent years. The differences between groups can be judged intuitively and superficially through principal component analysis (PCA) multi-dimensional score plots, but there is a lack of scientific and quantitative index to quantify the differences between groups. How to quantify the difference between groups is basically a blank area of research. Based on traditional F-statistic, we proposed a new F*-statistic to quantify the difference between groups in PCA score plots from the perspective of statistics. As the results revealed, the calculated F*-statistic was 2.58, smaller than the critical value 3.17 (α = 0.05), which indicated that there was no significant difference between groups. Our study add another dimension for PCA application, which offers a new strategy to quantify differences between groups by a new perspective, namely, a combination of fingerprint, chemometrics and statistics to evaluate inter-batches quality consistency quantitatively and objectively. Therefore, this manuscript could provide new ideas and technical references for the quality consistency evaluation of natural drugs, thus better guarantee their clinical efficacy and safety, and better promote industrial development.

Gait variability between younger and older adults: An equality of variance analysis.

BACKGROUND: To estimate gait variability, several methods have been routinely used which provide a measure of global variability. A recent study introduced a group waveform variability method which provides a point-by-point measurement of data variance equality. This can identify where in the gait cycle the significant differences in variability exist. RESEARCH QUESTION: Do waveform differences exist in equality of variance and group means in lower limb biomechanical variables between healthy younger and older adults during a gait task? METHODS: Twenty healthy younger (19-44 years old, age=29.9(7.0) years, body mass index= 24.6(3.2)kg/m2, females= 10) and 20 healthy older (55-79 years old, age=63.6(5.5) years, body mass index= 25.9(2.7)kg/m2, females= 10) adults who were free from lower limb injuries and had no musculoskeletal or neurological disorders. Temporospatial outcomes, sagittal and frontal lower limb joint angles and moments, along with joint powers were examined as participants walked at a self-selected pace. Waveform patterns were normalized to the gait cycle and compared using equality of variance and statistical parametric mapping techniques. RESULTS: No difference in walking speed existed between the younger or older groups (P > .05). The older group had greater variability (P < .05) in sagittal hip angles, as well as greater frontal ankle angle and moment variability. The younger group had significantly greater mean (P < .05) ankle power generation prior to toe-off. SIGNIFICANCE: This study provided a baseline of temporal differences in variance between healthy younger and older individuals. Its findings warrant the use of the equality of variance test to compare temporal differences for a variety of populations and tasks. Older adults generally had more variability than the younger adults, with many differences occurring near the transition from double- to single-limb support. The statistical parametric mapping analysis showed that the older adults could not generate as much ankle power as the younger adults prior to toe-off.

A waveform test for variance inequality, with a comparison of ground reaction force during walking in younger vs. older adults.

Various methods have been suggested for estimating the variability in biomechanical variables during gait. However, all current measures of variability are performed on discrete measurements extracted from the kinematic or kinetic waveforms, which provide no temporal information on where differences in variability occur. This study used a variance equality test to compare temporal differences in group variance along the entire ground reaction force waveform. The variance equality test used an F-statistic whose critical value was determined using the random field theory function within the one-dimensional statistical parametric mapping package. Twenty healthy younger and twenty older adults were included in the study and completed gait analysis as they walked along a level walkway at a self-selected pace. Variance for each group was calculated and compared at each interval along the waveform to produce the F-value. The F-value was compared against a calculated F-critical value to determine where in the waveform significant differences in ground reaction force variance occurred. Results suggest that younger individuals may exhibit greater ground reaction force variance during heel contact in the vertical and posterior directions, and that older individuals may exhibit greater variability in the mediolateral direction at toe-off. This study was able to identify differences in ground reaction force variance within the gait cycle between younger and older adults. The findings of this study warrant the use of the function as a suitable method to compare variance along the entire waveform between two groups.

Rest-activity circadian rhythms and bone mineral density in elderly men.

BACKGROUND: Disrupted rest-activity circadian rhythm (RAR) patterns have been associated with poor health outcomes (i.e. diminished cognitive function, increased risk of dementia and falls). Circadian time cues in bone influence the differentiation of osteoblasts and osteoclasts, and bone turnover markers exhibit circadian variation; relationships between bone outcomes and RAR are emerging areas of research. We evaluated associations between RAR and areal bone mineral density (aBMD) at the total hip and femoral neck in older men from the Osteoporotic Fractures in Men (MrOS) cohort. We hypothesized that weaker RAR patterns would be associated with lower aBMD. METHODS: MrOS is an ongoing prospective cohort study following ambulatory men ≥ 65 years (n = 5994) at 6 U.S. clinics (baseline enrollment 3/2000-4/2002); participants for this analysis are from an ancillary study, Outcomes of Sleep Disorders in Older Men (MrOS Sleep). We included data from men who had technically adequate measures of RAR and aBMD at Sleep Visit 1 (12/2003-3/2005), with repeat aBMD at core Visit 3 (3/2007-3/2009) (n = 2412; mean age at Sleep Visit 1: 75.7 ± 5.2 years). aBMD was measured by dual energy x-ray absorptiometry (DXA). Actigraphs worn on the non-dominant wrist were used to collect circadian activity data over 4.8 ± 0.8 consecutive 24-hour periods. An extension of the traditional cosine curve was used to fit RAR to the activity data [Ancoli-Israel et al., 2003; Marler et al., 2006]. Six RAR parameters were evaluated: acrophase (time of peak activity), amplitude (rhythm strength), mesor (mean of activity fitted curve), pseudo F-statistic (overall circadian rhythmicity of rest and activity), alpha statistic (daytime to nighttime activity ratio), and beta statistic (daytime activity). Associations between RAR and aBMD (Sleep Visit 1), and RAR and ΔaBMD (Sleep Visit 1-Visit 3) were assessed with generalized linear models. Covariates included age, clinic site, physical activity, race, comorbidity, body mass index (BMI), smoking, alcohol, caffeine, beta blocker use, serum 25(OH) vitamin D and urinary melatonin and calcium. RESULTS: Pseudo F-statistic was significantly associated with total hip aBMD (p-trend = 0.009), femoral neck aBMD (p-trend = 0.007) and total hip ΔaBMD (p-trend = 0.017) in minimally adjusted models but not after multivariate (MV) adjustment. Alpha statistic was significantly associated with femoral neck aBMD (p-trend = 0.029) and femoral neck ΔaBMD (p-trend = 0.019) in minimally adjusted models; significance was retained in the femoral neck ΔaBMD model (p-trend = 0.034) after MV adjustment. There were no consistent, significant associations between the other RAR variables and aBMD or ΔaBMD. CONCLUSIONS: The data demonstrate modest associations between overall circadian rhythmicity of rest and activity (measured by pseudo F-statistic), as well as daytime to nighttime activity ratio (measured by alpha statistic), aBMD and ΔaBMD, but adjustment for covariates related to lifestyle, BMI and comorbidities attenuated most of these associations. These results suggest that RAR patterns are not independently associated with aBMD or four-year ΔaBMD at the total hip or femoral neck in older men, but additional research is needed.

Developing a new nonbinary SNP fluorescent multiplex detection system for forensic application in China.

Nonbinary single-nucleotide polymorphisms (SNPs) are potential forensic genetic markers because their discrimination power is greater than that of normal binary SNPs, and that they can detect highly degraded samples. We previously developed a nonbinary SNP multiplex typing assay. In this study, we selected additional 20 nonbinary SNPs from the NCBI SNP database and verified them through pyrosequencing. These 20 nonbinary SNPs were analyzed using the fluorescent-labeled SNaPshot multiplex SNP typing method. The allele frequencies and genetic parameters of these 20 nonbinary SNPs were determined among 314 unrelated individuals from Han populations from China. The total power of discrimination was 0.9999999999994, and the cumulative probability of exclusion was 0.9986. Moreover, the result of the combination of this 20 nonbinary SNP assay with the 20 nonbinary SNP assay we previously developed demonstrated that the cumulative probability of exclusion of the 40 nonbinary SNPs was 0.999991 and that no significant linkage disequilibrium was observed in all 40 nonbinary SNPs. Thus, we concluded that this new system consisting of new 20 nonbinary SNPs could provide highly informative polymorphic data which would be further used in forensic application and would serve as a potentially valuable supplement to forensic DNA analysis.