Hierarchical Hidden Markov Model in Detecting Activities of Daily Living in Wearable Videos for Studies of Dementia

International audienceThis paper presents a method for indexing activities of daily living in videos obtained from wearable cameras. In the context of dementia diagnosis by doctors, the videos are recorded at patients' houses and later visualized by the medical practitioners. The videos may last up to two hours, therefore a tool for an efficient navigation in terms of activities of interest is crucial for the doctors. The specific recording mode provides video data which are really difficult, being a single sequence shot where strong motion and sharp lighting changes often appear. Our work introduces an automatic motion based segmentation of the video and a video structuring approach in terms of activities by a hierarchical two-level Hidden Markov Model. We define our description space over motion and visual characteristics of video and audio channels. Experiments on real data obtained from the recording at home of several patients show the difficulty of the task and the promising results of our approach

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity and Hormone-Related Risk Factors

BACKGROUND: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. RESULTS: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)). CONCLUSIONS: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility

Association Between Menopausal Estrogen-Only Therapy and Ovarian Carcinoma Risk

OBJECTIVE: To describe the association between postmenopausal estrogen-only therapy use and risk of ovarian carcinoma, specifically with regard to disease histotype and duration and timing of use. METHODS: We conducted a pooled analysis of 906 women with ovarian carcinoma and 1,220 women in a control group; all 2,126 women included reported having had a hysterectomy. Ten population-based case-control studies participating in the Ovarian Cancer Association Consortium, an international consortium whose goal is to combine data from many studies with similar methods so reliable assessments of risk factors can be determined, were included. Self-reported questionnaire data from each study were harmonized and conditional logistic regression was used to examine estrogen-only therapy's histotype-specific and duration and recency of use associations. RESULTS: Forty-three and a half percent of the women in the control group reported previous use of estrogen-only therapy. Compared with them, current or recent estrogen-only therapy use was associated with an increased risk for the serous (51.4%, odds ratio [OR] 1.63, 95% confidence interval [CI] 1.27-2.09) and endometrioid (48.6%, OR 2.00, 95% CI 1.17-3.41) histotypes. In addition, statistically significant trends in risk according to duration of use were seen among current or recent postmenopausal estrogen-only therapy users for both ovarian carcinoma histotypes (Ptrend<.001 for serous and endometrioid). Compared with women in the control group, current or recent users for 10 years or more had increased risks of serous ovarian carcinoma (36.8%, OR 1.73, 95% CI 1.26-2.38) and endometrioid ovarian carcinoma (34.9%, OR 4.03, 95% CI 1.91-8.49). CONCLUSION: We found evidence of an increased risk of serous and endometrioid ovarian carcinoma associated with postmenopausal estrogen-only therapy use, particularly of long duration. These findings emphasize that risk may be associated with extended estrogen-only therapy use

Investigation of Exomic Variants Associated with Overall Survival in Ovarian Cancer

BACKGROUND: While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC). METHODS: The primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped). RESULTS: No individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E-6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E-6; Pcorrected = 0.01). CONCLUSIONS: Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed. IMPACT: This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid (p = 0.082) and clear cell (p = 0.083), with the most significant gene level association seen with TGFBR2 (p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 (p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA (p = 0.035, endometrioid and mucinous), LGALS1 (p = 0.03, mucinous), STAT5B (p = 0.022, clear cell), TGFBR1 (p = 0.021 endometrioid) and TGFBR2 (p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients

Distinct clinical and neuropathological features of G51D SNCA mutation cases compared with SNCA duplication and H50Q mutation

Background: We and others have described the neurodegenerative disorder caused by G51D SNCA mutation which shares characteristics of Parkinson’s disease (PD) and multiple system atrophy (MSA). The objective of this investigation was to extend the description of the clinical and neuropathological hallmarks of G51D mutant SNCA-associated disease by the study of two additional cases from a further G51D SNCA kindred and to compare the features of this group with a SNCA duplication case and a H50Q SNCA mutation case. Results: All three G51D patients were clinically characterised by parkinsonism, dementia, visual hallucinations, autonomic dysfunction and pyramidal signs with variable age at disease onset and levodopa response. The H50Q SNCA mutation case had a clinical picture that mimicked late-onset idiopathic PD with a good and sustained levodopa response. The SNCA duplication case presented with a clinical phenotype of frontotemporal dementia with marked behavioural changes, pyramidal signs, postural hypotension and transiently levodopa responsive parkinsonism. Detailed post-mortem neuropathological analysis was performed in all cases. All three G51D cases had abundant α-synuclein pathology with characteristics of both PD and MSA. These included widespread cortical and subcortical neuronal α-synuclein inclusions together with small numbers of inclusions resembling glial cytoplasmic inclusions (GCIs) in oligodendrocytes. In contrast the H50Q and SNCA duplication cases, had α-synuclein pathology resembling idiopathic PD without GCIs. Phosphorylated α-synuclein was present in all inclusions types in G51D cases but was more restricted in SNCA duplication and H50Q mutation. Inclusions were also immunoreactive for the 5G4 antibody indicating their highly aggregated and likely fibrillar state. Conclusions: Our characterisation of the clinical and neuropathological features of the present small series of G51D SNCA mutation cases should aid the recognition of this clinico-pathological entity. The neuropathological features of these cases consistently share characteristics of PD and MSA and are distinct from PD patients carrying the H50Q or SNCA duplication

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P ( )P≥5.0 ×10 (-)  (7)) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 (-)  (5); PSKAT-o = 9.23 × 10 (-)  (4)) and KRT13 (PAML = 1.67 × 10 (-)  (4); PSKAT-o = 1.07 × 10 (-)  (5)), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease