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Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Yang Ming University | Huang N.E.,National Central University | Peng C.-K.,Beth Israel Deaconess Medical Center | And 3 more authors.
PLoS ONE | Year: 2010

Background: Seasonal depression has generated considerable clinical interest in recent years. Despite a common belief that people in higher latitudes are more vulnerable to low mood during the winter, it has never been demonstrated that human's moods are subject to seasonal change on a global scale. The aim of this study was to investigate large-scale seasonal patterns of depression using Internet search query data as a signature and proxy of human affect. Methodology/Principal Findings: Our study was based on a publicly available search engine database, Google Insights for Search, which provides time series data of weekly search trends from January 1, 2004 to June 30, 2009. We applied an empirical mode decomposition method to isolate seasonal components of health-related search trends of depression in 54 geographic areas worldwide. We identified a seasonal trend of depression that was opposite between the northern and southern hemispheres; this trend was significantly correlated with seasonal oscillations of temperature (USA: r =20.872, p,0.001; Australia: r =20.656, p,0.001). Based on analyses of search trends over 54 geological locations worldwide, we found that the degree of correlation between searching for depression and temperature was latitude-dependent (northern hemisphere: r =20.686; p,0.001; southern hemisphere: r = 0.871; p,0.0001). Conclusions/Significance: Our findings indicate that Internet searches for depression from people in higher latitudes are more vulnerable to seasonal change, whereas this phenomenon is obscured in tropical areas. This phenomenon exists universally across countries, regardless of language. This study provides novel, Internet-based evidence for the epidemiology of seasonal depression. © 2010 Yang et al.


Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Yang Ming University | Chen T.-J.,I - Shou University | Tsai S.-J.,I - Shou University | And 7 more authors.
American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics | Year: 2010

A common polymorphism of the brain-derived neurotrophic factor (BDNF) gene (Val66Met) has been implicated in anxiety, which is associated with lower vagal activity. We hypothesize that the BDNF Val66Met polymorphism may have a modulatory effect on the cardiac sympathovagal balance. A total of 211 healthy Chinese-Han adults (58 male, 153 female, aged 33.3 ± 10.3 years) were recruited with three BDNF genotypes: Val/Val (47, 22.3%), Val/Met (108, 51.2%), and Met/Met (56, 26.5%). Autonomic function was assessed via an analysis of heart rate variability. Reductions in high-frequency power, an index for parasympathetic activity, and increases in the low-frequency/high-frequency ratio, an index for sympathovagal balance, were found in subjects bearing the Met/Met genotype as compared to the Val/Val group. These results suggest that an altered sympathovagal balance with relatively decreased parasympathetic activity is associated with the Met/Met genotype, suggesting a potential role for the studied BDNF polymorphism in modulating cardiac autonomic functions. © 2010 Wiley-Liss, Inc.


Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Yang Ming University | Yang A.C.,National Central University | Tsai S.-J.,Taipei Veterans General Hospital | And 3 more authors.
Journal of Affective Disorders | Year: 2011

Background: Although Internet has become an important source for affected people seeking suicide information, the connection between Internet searches for suicide information and suicidal death remains largely unknown. This study aims to evaluate the association between suicide and Internet searches trends for 37 suicide-related terms representing major known risks of suicide. Methods: This study analyzes suicide death data in Taipei City, Taiwan and corresponding local Internet search trend data provided by Google Insights for Search during the period from January 2004 to December 2009. The investigation uses cross correlation analysis to estimate the temporal relationship between suicide and Internet search trends and multiple linear regression analysis to identify significant factors associated with suicide from a pool of search trend data that either coincides or precedes the suicide death. Results: Results show that a set of suicide-related search terms, the trends of which either temporally coincided or preceded trends of suicide data, were associated with suicide death. These search factors varied among different suicide samples. Searches for "major depression" and "divorce" accounted for, at most, 30.2% of the variance in suicide data. When considering only leading suicide trends, searches for "divorce" and the pro-suicide term "complete guide of suicide," accounted for 22.7% of variance in suicide data. Conclusions: Appropriate filtering and detection of potentially harmful source in keyword-driven search results by search engine providers may be a reasonable strategy to reduce suicide deaths. © 2011 Elsevier B.V. All rights reserved.


Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Central University | Yang A.C.,National Yang Ming University | Tsai S.-J.,National Yang Ming University | And 9 more authors.
PLoS ONE | Year: 2011

Background: Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype-phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods: A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results: With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions: We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control. © 2011 Yang et al.


Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Yang Ming University | Yang A.C.,National Central University | Fuh J.-L.,Taipei Veterans General Hospital | And 7 more authors.
PLoS ONE | Year: 2011

Background: Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings: The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance: Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons. © 2011 Yang et al.


Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Yang Ming University | Tsai S.-J.,National Yang Ming University | Tsai S.-J.,Taipei Veterans General Hospital | Huang N.E.,National Central University
Journal of Affective Disorders | Year: 2011

Background: Research has implicated environmental risk factors, such as meteorological variables, in suicide. However, studies have not investigated air pollution, known to induce acute medical conditions and increase mortality, in suicide. This study comprehensively assesses the temporal relationship between suicide and air pollution, weather, and unemployment variables in Taipei City from January 1 1991 to December 31 2008. Methods: This research used the empirical mode decomposition (EMD) method to de-trend the suicide data into a set of intrinsic oscillations, called intrinsic mode functions (IMFs). Multiple linear regression analysis with forward stepwise method was used to identify significant predictors of suicide from a pool of air pollution, weather, and unemployment data, and to quantify the temporal association between decomposed suicide IMFs with these predictors at different time scales. Results: Findings of this study predicted a classic seasonal pattern of increased suicide occurring in early summer by increased air particulates and decreased barometric pressure, in which the latter was in accordance with increased temperature during the corresponding time. Gaseous air pollutants, such as sulfur dioxide and ozone, were found to increase the risk of suicide at longer time scales. Decreased sunshine duration and sunspot activity predicted the increased suicide. After controlling for the unemployment factor, environmental risks predicted 33.7% of variance in the suicide data. Conclusions: Using EMD analysis, this study found time-scale dependent associations between suicide and air pollution, weather and unemployment data. Contributing environmental risks may vary in different geographic regions and in different populations. © 2010 Elsevier B.V. All rights reserved.


Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Yang Ming University | Yang A.C.,Beth Israel Deaconess Medical Center | Yang C.-H.,National Yang Ming University | And 10 more authors.
Psychophysiology | Year: 2011

Sleep disruption is an important aspect of major depressive disorder but lacks an objective and inexpensive means of assessment. We evaluated the utility of electrocardiogram (ECG)-based cardiopulmonary coupling analysis to quantify physiologic sleep stability in patients with major depression. Relative to controls, unmedicated depressed patients had a reduction in high-frequency coupling, an index of stable sleep, an increase in low-frequency coupling, an index of unstable sleep, and an increase in very-low-frequency coupling, an index of wakefulness/REM sleep. The medicated depressed group showed a restoration of stable sleep to a level comparable with that of the control group. ECG-based cardiopulmonary coupling analysis may provide a simple, cost-efficient point-of-care method to quantify sleep quality/stability and to objectively evaluate the severity of insomnia in patients with major depression. Copyright © 2010 Society for Psychophysiological Research.


Yang A.C.,Chu Tung Veterans Hospital | Yang A.C.,National Central University | Yang A.C.,National Yang Ming University | Tsai S.-J.,National Yang Ming University | And 8 more authors.
Journal of Affective Disorders | Year: 2011

Background: Depression is known to be associated with altered cardiovascular variability and increased cardiovascular comorbidity, yet it is unknown whether altered cardiac autonomic function in depression is associated with insomnia, a common symptom comorbid with depression. This study aimed to investigate the long-term diurnal profile of autonomic function as measured by heart rate variability (HRV) in both major depression and primary insomnia patients. Method: A total of 52 non-medicated patients with major depression, 47 non-medicated patients with primary insomnia, and 88 matched controls without insomnia were recruited. Each subject was assessed by means of sleep and mood questionnaires and underwent twenty-four-hour ambulatory electrocardiogram monitoring. Standard HRV analysis and a well-validated complexity measure, multiscale entropy, were applied to comprehensively assess the diurnal profiles of autonomic function and physiologic complexity in our study sample. Results: Compared with the controls, the patients with major depression and those with primary insomnia exhibited significant reductions in parasympathetic-related HRV indices, and this association was mainly driven by the presence of poor sleep. Both groups of patients also exhibited significant reductions in physiologic complexity during the sleep period as compared with the healthy controls. Alterations in HRV indices were correlated with perceived sleep questionnaire scores but not with depression scales. Conclusions: Our findings suggest a pivotal role of sleep disturbance in regulating cardiovascular variability in major depression and primary insomnia patients. These findings could highlight the importance of treating insomnia as an independent disease rather than a symptom. © 2010 Elsevier B.V. All rights reserved.


PubMed | Chu Tung Veterans Hospital
Type: Journal Article | Journal: PloS one | Year: 2011

Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area.The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts.Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons.


PubMed | Chu Tung Veterans Hospital
Type: Journal Article | Journal: PloS one | Year: 2011

Genetic polymorphisms in the gene encoding the -adrenergic receptors (-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype-phenotype analysis to investigate the association between -AR gene polymorphisms and heart rate dynamics.A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6 10.8 years, range 19 to 63 years) were recruited and genotyped for three common -AR polymorphisms: (1)-AR Ser49Gly, (2)-AR Arg16Gly and (2)-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects.With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of (2)-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity.We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with -AR polymorphisms. Our results provide evidence that (2)-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control.

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