•In this issue (April 2015)•
This issue starts with a special article by Paul Bebbington[1]and two commentaries on the article, one by Jim van Os[2]and one by Xin Yu.[3]Bebbington’s article discusses how research over the last 20 years in psychosocial epidemiology and cognitive behaviour therapy has led to new thinking about the etiology and development of psychoses. Despite the frequently reported centrality of heritable genetic factors, social environment and the occurrence of so-called nonpsychotic symptoms such as disturbances in affect and sleep play key roles in the onset and persistence of psychotic disorders. These findings have important implications for our understanding of the multiple pathways that lead to psychotic symptoms and, more importantly, for the development of interventions that can prevent or ameliorate these symptoms. Van Os highlights the diagnostic implications of this revised understanding of psychosis. If psychosis is a ‘transdiagnostic dimension’, that is, a category of symptoms that refect severity in a variety of diagnostc categories, then the rigid psychotc versus non-psychotc dichotomy that has dominated diagnostc consideratons for decades needs to be re-considered. This dimensional approach was considered in the preliminary discussions of DSM-5 but was eventually dropped because of the complexity of integrating dichotomous diagnoses and dimensional scores; van Os believes that integrating both approaches is necessary to improving our understanding of how symptoms interact with each other and respond to environmental infuences.[4]Yu Xin considers the mult-dimensional approach to diagnoses proposed by Bebbington a substantal improvement on the traditional dichotomous classification system, but remains concerned about the lack of methodological rigor of assessment methods of concurrent psychotic and non-psychotc symptoms. He is also skeptcal about the use of the presence of concurrent non-psychotic symptoms or responsiveness to cognitive behavioral therapy as parameters for sub-classifying psychotic disorders.
The review article by Freedman and Ross[6]raises the enticing possibility that prenatal dietary supplementation with phosphatidyl-choline could prevent the subsequent development of schizophrenia, similar to prenatal folate supplementation to prevent clef palate and spina bifda.[7,8]The authors integrate a small but growing literature with fndings from their own studies to suggest that cholinergic neurotransmission at nicotinic receptors is essential to normal brain circuit development and, more importantly, that choline supplementation in the second and third trimesters is associated with improved inhibitory neuronal functons—functons that are associated with schizophrenia and attention deficit disorder. Given the long tme-lag between the interventon and the target outcome (schizophrenia), providing convincing proof of the benefit of prenatal choline supplementation will be difficult. But the huge potential public health benefits of this simple, safe, inexpensive, and shortterm interventon may be sufcient to justfy promotng choline supplementation before definitive proof of its efcacy is available.
The first original research article in this issue by Xie and colleagues[9]is a randomized controlled trial involving the administration of ‘shuganjieyu’, the first Chinese traditional medicine approved for use in the treatment of depression by the Chinese drug regulatory authorities. The efficacy and safety of shuganjieyu, which is composed of St. John’s wort and extracts of Siberian ginseng, has been reported in previous studies.[10,11]The current study assesses the relative efficacy of shuganjieyu with or without adjunctive repetitive transcranial magnetic stimulation (rTMS) in the treatment of 65 elderly inpatents with depression. All participants received daily shuganjieyu and were randomly assigned to active or sham rTMS treatment (5 days a week for 4 weeks). The trial continued for 6 weeks but only 1 patient dropped out of the experimental group and 2 patients from the control group. None of the participants had serious adverse effects. Blinded assessment of outcome using the Hamilton Ratng Scale for Depression (HAMD-17) found that both groups improved significantly after the first 2 weeks of treatment, but after 6 weeks of treatment only one-fifth of participants had a greater than 50% drop in the severity of depression from baseline. There were no significant differences between groups, so there appears to be no beneft of combined treatment with shuganjieyu and rTMS. The relatvely low 20% rate of substantal improvement afer 6 weeks of treatment suggests that further placebo-controlled trials with shuganjieyu are needed.
The second original research article by Zuo and colleagues[12]is a secondary data analysis that uses both gene-based and pathway-based methods to analyze data from several large genome-wide-associationstudies (GWAS) of alcohol dependence. Though more complicated, gene-based and pathway-based methods have several advantages over the more traditional single nucleotde polymorphism (SNP) method; it is, for example, easier to associate biological functions with specifc genes and pathways than with specifc SNPs. The combined dataset used in the analysis included 1409 European-American and 681 African-American alcohol dependent individuals and 1518 European-American and 508 African-American healthy controls. After applying statistical adjustments, the ‘cell-extracellular matrix interactions’ pathway and the PXNgene (which encodes paxillin) within this pathway were the most promising risk factors for alcohol dependence. This new analytic approach identified several genes and signalling pathways of potental importance to the onset and development of alcohol dependence that are not evident when limitng the analysis to SNPs.
The forum addresses an issue of increasing importance in China and other rapidly aging middleincome countries: the diagnosis of Alzheimer’s disease
(AD). Yang and Xiao[13]discuss how substantal advances over the last 2 decades in the understanding of the etology and progressive deterioraton characteristc of AD have led to refnements in the diagnostc criteria for AD. However, these criteria now require highly trained clinicians to make fine clinical distinctions and, often, advanced equipment to assess the presence of an increasing number of potental biomarkers. The criteria are, therefore, of litle use in locatons where high-level clinicians and advanced equipment are not available. Chen[15]concurs that the new criteria are of little practical use in routine care and highlights the ethical problems of making early diagnoses for a conditon for which there is, as yet, not efectve treatment. However, he believes that biomarkers are essental in clinical and pharmacological research about AD because their use allows for a more precise identfcaton of the conditon, earlier institution of treatment, and more accurate assessment of the efectveness of proposed treatments.
The case report from India by Sachdeva and colleagues[15]described a 36-year-old patient with an 8-year history of moderately severe social phobia and agoraphobia with panic attacks who had experienced concurrent visual and auditory hallucinations that occurred multple tmes a day over the 2 months prior to admission. Treatment of the anxiety disorder with sertraline over 4 weeks significantly improved the anxiety symptoms; the hallucinations also resolved completely over this 4-week period—without resorting to the use of antipsychotic medication. This case provides support for the approach to psychosis promoted by Bebbington in this issue’s special artcle[1]and by van Os in the commentary;[2]they consider psychosis a transdiagnostic dimensional group of symptoms that are often markers of the severity of underlying disorders.
The biostatistics in psychiatry piece by Song and Lu[16]introduces the decision tree method that is particularly useful for identifying homogenous subgroups of subjects in large complex data sets and for developing prediction algorithms for outcomes of interest. This non-parametric analytic method has fewer underlying assumptions than other methods so it is beter able to deal with data sets that have missing values and to rank the relatve importance of diferent potential predictor variables. The article provides a general descripton of the method and of the available algorithms and sofware packages for building decision tree models.
[Shanghai Arch Psychiatry. 2015; 27(2): 68-69. doi: htp://dx.doi.org/10.11919/j.issn.1002-0829.215047]
1. Bebbington P. Unravelling psychosis: psychosocial epidemiology, mechanism, and meaning. Shanghai Arch Psychiatry. 2015; 27(2): 70-81. Epub 2015 Apr 2. doi:htp:// dx.doi.org/10.11919/j.issn.1002-0829.215027
2. Van Os J. The transdiagnostic dimension of psychosis: implicatons for psychiatric nosology and research. Shanghai Arch Psychiatry. 2015; 27(2): 82-86. doi:http://dx.doi. org/10.11919/j.issn.1002-0829.215041
3. Yu X. Finding a solution to psychosis: the emergence of a new path. Shanghai Arch Psychiatry. 2015; 27(2): 87-89. doi: htp://dx.doi.org/10.11919/j.issn.1002-0829.215043
4. van Os J. The dynamics of subthreshold psychopathology: implications for diagnosis and treatment. Am J Psychiatry 2013; 170: 695-698. doi: http://dx.doi.org/10.1176/appi. ajp.2013.13040474
5. van Os J, Lataster T, Delespaul P, Whichers M, Myin-Germeys I. Evidence that a psychopathology interactome has diagnostc value, predictng clinical needs: an experience sampling study. PLoS One. 2014; 9: e86652. doi: http:// dx.doi.org/10.1371/journal.pone.0086652
6. Freedman R, Ross RG. Prenatal choline and the development of schizophreniaShanghai Arch Psychiatry. 2015; 27(2): 90-102. doi: http://dx.doi.org/10.11919/ j.issn.1002-0829.215006
7. Wilcox AJ, Lie RT, Solvoll K, Taylor J, McConnaughey DR, Abyholm F, et al. Folic acid supplements and risk of facial clefts: national population based case-control study. BMJ. 2007; 334: 464. doi: http://dx.doi.org/10.1136/ bmj.39079.618287.0B
8. MRC Vitamin Study Research Group. Prevention of neural tube defects: Results of the medical research council vitamin study. Lancet. 1991; 338: 131–137
9. Xie MM, Jiang WH, Yang HB. Efficacy and safety of the Chinese herbal medicine shuganjieyu with and without adjunctive repetitive transcranial magnetic stimulation (rTMS) for geriatric depression: a randomized controlled trial. Shanghai Arch Psychiatry. 2015; 27(2): 103-110. doi: htp://dx.doi.org/10.11919/j.issn.1002-0829.214151
10. Liu SB, Li CF, Wang YF, Li J. [Case-control study of the treatment of Shuganjieyu capsule combined with venlafaxine on the elderly patients with depression]. Lin Chuang Jing Shen Yi Xue Za Zhi. 2012; 22(2): 98. Chinese
11. Song H, Ma JD, Chen YX, Huang SP. [The efficacy of Shuganjieyu capsule combined with venlafaxine in treatment of senile depression]. Yi Xue Zong Shu. 2013; 19(17): 2302-2308. Chinese. doi: htp://dx.doi.org/10.3969/ j.issn.1006-2084.2013.17.043
12. Zuo LJ, Zhang CZ, Sayward FG, Cheung KH, Wang KS, Krystal JH, et al. Gene-based and pathway-based genomewide association study of alcohol dependence. Shanghai Arch Psychiatry. 2015; 27(2): 111-118. doi: http://dx.doi. org/10.11919/j.issn.1002-0829.215031
13. Yang CC, Xiao SF. Are the revised diagnostic criteria for Alzheimer’s disease useful in low- and middle-income countries? Shanghai Arch Psychiatry. 2015; 27(2): 119-123. doi: htp://dx.doi.org/10.11919/j.issn.1002-0829.215001
14. Chen W. Clinical and research value of the new diagnostic criteria for Alzheimer’s disease. Shanghai Arch Psychiatry. 2015; 27(2): 124-125. doi: http://dx.doi.org/10.11919/ j.issn.1002-0829.215046
15. Sachdeva A, Saxena A, Kandpal M. Case report of visual halluncinations in anxiety. Shanghai Arch Psychiatry. 2015; 27(2): 126-129. doi: http://dx.doi.org/10.11919/ j.issn.1002-0829.215011
16. Song YY, Lu Y. Decision tree methods: applications for classification and prediction. Shanghai Arch Psychiatry. 2015; 27(2): 130-135. doi: http://dx.doi.org/10.11919/ j.issn.1002-0829.215044
A full-text Chinese translation of this article will be available at http://dx.doi.org/10.11919/j.issn.1002-0829.215047 on June 6, 2015.