17 05 12 Bertolino rischio-geneticopsichiatriamilano2017.it/.../17_05_12_BERTOLINO_rischio-genetico.pdf · La pleiotropia in psichiatria funzionealteratadi un gene che influenza diversitratti

Convegno Nazionale GISDI GISDAP Milano 11 – 13 maggio 2017

Responsabilità Professionale e Danno alla Persona in Psichiatria 1

Rischio genetico e meccanismi cerebrali di psicosi

Alessandro Bertolino, M.D., Ph.D.

Group of Psychiatric Neuroscience

Department of Psychiatry

Department of Basic Medical Science, Neuroscience and Sense Organs

University of Bari, ‘Aldo Moro’,

Italy

[email protected]

Outline

•The categorical diagnosis

•Beyond categorization: the Spectrum and the Research Domain Criteria

(RDoC) dimensions

2

•The etiology

•Conclusions



Outline

•The categorical diagnosis


(RDoC) dimensions

3

•The etiology

•Conclusions

The history of Schizophrenia

Emil Kraepelin: dementia praecox and manic‐depression

Bleuler: the four A’s (affect, ambivalence, autism, thought association)

Schneider: first‐rank symptoms

Rosenhan’s pseudopatients and reliability of diagnosis

4

DSM III: the reification of symptoms

Crow and Andreasen

DSM V



Early identification: Ultra High Risk criteria

Between the ages of 15 and 30, these criteria identify three UHR groups based on intensity, frequency and duration of symptoms,

1. APS, attenuated psychotic symptoms

2. BLIPS, brief limited intermittent psychotic symptoms

3. Genetic vulnerability together with significant decline of functioning from baseline (TSRF, trait and state risk factors) and non‐specific prodromal symptoms (UPS).

Attempts at diagnosis of Bipolar Disorder

• Hippocrates – Melancholia and Mania

• Falret and Baillarger 1851 – Folie Circulaire

• Khalbaum and Krepelin – Manic depressive insanity

• DSM‐I, 1952: Manic Depressive Reactions

• DSM II 1968: Manic Depressive Illness• DSM‐II, 1968: Manic‐Depressive Illness

• DSM‐III, 1980: Manic Episode and Bipolar Disorder

• DSM‐IV, 1994: Bipolar Disorder and a Mixed Episode

• DSM‐5, 2013



Limitations of present diagnostic categorization

• No pathognomonic symptoms

• Heterogenity of clinical presentation

• No biological validity or validation

• Overlap between different categories

Outline

•The diagnosis of Bipolar Disorder


(RDoC) dimensions

8

•The etiology

•Conclusions



Categories vs dimensions

• DSM – sharp definition of boundaries between categories

• The Bipolar Spectrum: mood and temperament are in a continuum within which the emotions of sadness and happiness can wax and wane shifting from physiology to pathology. The bipolar spectrum model suggests that several patient presentations not currently recognized by the DSM warrant consideration as part of a mood disorders continuum. These include hypomania or mania associated with antidepressants; manic symptoms which fall short of the current DSM threshold for hypomania; and depression attended by multiple non‐manic markers that are associated with bipolar course.

Evidence supporting the Spectrum concept

• no sharp boundaries exist between mania or depressiond l iand normal experience;

• current understanding about risk factors for bipolardisorder – non specific, additive and complex

• the diathesis‐stress model and the role of temperament;

• mounting empiric evidence from epidemiologic and clinical studies that spectrum presentations of bipolardisorder exist, fall along a continuum, and are oftenassociated with profound impairment.



Why have the Research Domain Criteria been generated?

• An increasingly comprehensive body of research in genetics• An increasingly comprehensive body of research in genetics, neuroscience, and behavioral science has transformed our understanding of how the brain produces adaptive behavior and its disruption.

• However, new findings on mental disorders have had limited li i l i t tl b th l d t l tclinical impact, partly because they map only moderately onto current diagnostic categories for mental illness.

• RDoC represents the beginning of a long‐term project to allow neuroscience‐based classification.

Research Domain Criteria (RDoC)

The objective of RDoC is to foster research to validate dimensions defined by neurobiology and behavioral measures that cut across current disorder gycategories, and that can inform future revisions of our diagnostic systems.

For a dimension to be included, evidence was needed

a) for the dimension to be a validated behavioral function;

b) for a neural circuit or system to play a preponderant role in implementing ) y p y p p p gthe function.



The RDoC matrix ‐ Domains, constructs and units of analysis

RDoC: Domains and constructsPositive Valence Systems

1. Approach motivation2. Initial responsiveness to reward attainment 3. Sustained/Longer‐term responsiveness toreward attainment

Arousal and Regulatory Systems

1. Arousal2. Circadian Rhythms3. Sleep and wakefulness4 Default Mode Networkreward attainment

4. Reward Learning5. Habit

Negative Valence Systems

1. Responses to acute threat (Fear)2. Responses to potential harm (Anxiety)3. Responses to sustained threat4. Frustrative non‐reward

4. Default Mode Network

Cognitive Systems

1. Attention2. Perception3. Declarative Memory4. Language5. Cognitive Control6. Working Memory

5. LossSocial Processes

1. Affiliation and Attachment2. Social Communication3. Perception and Understanding of Self4. Perception and Understanding of Others



Constructs and circuitsCircuits represent the core aspect of RDoC because they are central to all levels of biology

1.Negative Valence – Threat (e.g.,

Amygdala, Sub-genual Cingulate)

2.Positive Valence – Reward (e.g.,

Striatum, mesolimbic dopamine system)

3.Cognitive Systems/Working Memory –Dorsolateral Prefrontal Cortex

4.Systems for Social Processes - Facial expression recognition (e.g., ventral visual stream, fusiform gyrus)

5.Arousal/Regulatory processes -Readiness for stimulus processing and responding (e.g., brain resting state network)

Adapted from Meyer – Lindenberg and Weinberger, 2006

The phenotype of PFC dysfunction in Schizophrenia

Callicott et al. Am J Psychiatry 2003Callicott et al. Cerebral Cortex 2000



Neural dysfunction during emotion processing in BP

Phillips Am J Psychiatry 2014

Limitations of the RDoC approach

• Diagnosis may be as difficult as if using categorical approaches

• Oversimplification of psychopathology – amygdala reactivity and negativeOversimplification of psychopathology amygdala reactivity and negative valence, DLPFC reactivity and cognition

• No definition of disease

• Psychosis and Depression

• Longitudinal profile of change (TIME)

• Brain circuits in animal models do not fully reflect circuits of humansBrain circuits in animal models do not fully reflect circuits of humans



Outline



(RDoC) dimensions

19

•The etiology

•Conclusions

Heritability of Psychiatric Disorders ‐ They are likely caused by a combination of common variants with small effect and highly

penetrant rare variants

Tsuji Human Mol Genetics 2010Sullivan et al Nature Reviews Genetics 2012



Signaling pathwaysThe D2 cAMP‐independent pathway includes some of the

usual suspects

Li and Jope, Neuropsychopharm 2010



Functional genetic variation within HTR2A, systems level phenotypes and response to treatment

Blasi et al., JAMA Psychiatry 2013

Interaction between DRD2 rs1076560 and Cannabis use on risk for Psychosis

Colizzi et al, Schizophrenia Bull 2015



Multiple variants of small effect contribute to risk for BPD

Purcell et al, Nature Genetics 2009

Genetic relationship between Schizophrenia and other Psychiatric Disorders

Lee et al, Nature Genetics 2013



La pleiotropia in psichiatriafunzione alterata di un gene che influenza diversi tratti

Antilla et al, BioRxiv 2017

Biological insights from 108 schizophrenia‐associated genetic loci

Up to 36,989 cases and 113,075 controls

>1.5 million genetic variables

DRD2

Ripke et al, Nature 2014



Genetics of Bipolar Disorder, the latest GWA iteration – 56 SNPs

Mühleisen et al. Nat Commun. 2014 Mar 11;5:3339.

ADCY2

Risk loci with shared effects on five major psychiatric disorders: GWA (Patients N=33k; Controls N 28k)

Smoller et al, Lancet 2013



Testing genetic association with neural activity supporting behavioral dimensions

Aims• Identify, with a data-driven approach, the brain regions under genetic control during emotionprocessing;• Identify single-nucleotide polymorphisms (SNPs) associated with activity in the brain areasunder genetic control.

With these aims:• In healthy twins, we located the areas whose functionality is mainly under genetic control;• In healthy non-twins we investigated the contribution of specific SNPs in explaining the varianceof those previously located areas.



Activity in Amygdala during emotion processing is highly heritable

Brain areas with the largest genetic component (ICC)z:

-22

ACE model0.540053 a2

0.396206 c2

0.06374 e2

ICC F p0.79936827 10.2497291 1.5688E-05

ICC and ACE model computation of combined left and right amygdala signals

x: -1

4, y

: 0, z

ICC=0.66 (p<0.001)

x: 2

4, y

: 0, z

: -18

ICC=0.83 (p<0.001)

a2=additive geneticsc2=common environmente2=unique environment

Quarto et al, in preparation

SimpleM = 0.05

One variant is associated with activity in Amygdala from GWAS

From the GWAS analysis, one SNP (rs1198575) survived the simpleM correction (Bonferroni correction based on the estimation of the number of effectively independent tests – Gao et al., 2008 Genetic Epidemiology) of p<0.05, with the C allele being associated with lower amygdala activity.

CC CT TT

Quarto et al, in preparation



rs1198575Chromosome 1:98562260

ENSEMBL v75 – Feb 2014ENSEMBL v75 Feb 2014

SNP is located in the 5´ region of the MIR137 host gene, at 51kbp from MIR137 and at 47kbp from the HG

rs1198575

rs1198575 is associated with risk for schizophrenia

The C allele of the rs1198575 has been associated with risk for schizophrenia in the genome-wide association study of the Psychiatric Genomics Consortium (Ripke et al., 2014 Nature).



DRD2Module as identified with WGCNADataset: Braincloud (Colantuoni et al. 2011, Nature)

hub genes DRD2 pathway related genes Network genes

Pergola, Di Carlo et al, Translational Psychiatry 2017

Rank Marker Gene Gene Name MAF

SNPs associated with expression of the whole DRD2 module

D2L coexpression genetic score

1 rs2486064 CHIT1 Chitinase 1 0,22

2 rs6902039 GPLD1 Glycosylphosphatidylinositol Specific Phospholipase D1 0,23

3 rs851436 OSR1 Odd‐Skipped Related 1 0,48

4 rs9297283 POP1 Processing Of Precursor 1, Ribonuclease P/MRP Subunit 0,20

5 rs12940715 SDK2 sidekick cell adhesion molecule 2 0,12

6 rs1805453 DHX33 DEAH (Asp‐Glu‐Ala‐His) Box Polypeptide 33 0,34

ll l i7 rs11213916 BTG4 B‐Cell Translocation Gene 4 0,30

8 rs1037791 AGR2 Anterior Gradient 2 0,31

Pergola, Di Carlo et al., Translational Psychiatry 2017



Genetic Score predicts brain activity during WMN=125, p < 0.05, corrected

N=244, p < 0.05, corrected

NSFG (BA 10)

Pergola et al, Transl Psychiatry, 2017

D2L PGS

SIGNALCHANGEIN

The association between treatment response and DRD2 PGS in schizophrenia (discovery and replication)

Rho=.39; p= .007 Rho= .27, p= .047



Bromocriptine changes the relationship between D2L genetic score and DLPFC activity only when GS is

considered as a quadratic term

D2L coexpression genetic score

Selvaggi, Pergola et al., submitted

Outline



(RDoC) dimensions

42

•The etiology

•Conclusions



The purpose of diagnostic validity

• making a correct prognosis

• performing correct treatment

• making correct predictions of outcome

Acknowledgements

Lieber Institute for Brain Development, JHU, Baltimore, MD, USA

GNP – DSNP

University of Bari Italy

Gianluca UrsiniVenkata S Mattay

Daniel R Weinberger

Giuseppe Blasi, Grazia Caforio, Annabella Di Giorgio, Giulio

Pergola, Antonio Rampino

Ileana Andriola, Linda Antonucci, Mariateresa Attrotto, Lucia

Colagiorgio, Marco Colizzi, Enrico D’Ambrosio, Pasquale Di Carlo,

Leonardo Fazio, Barbara Gelao, Riccarda Lomuscio, Luisa Longo,

Marina Mancini, Rita Masellis, Maria Antonietta Nettis,

Apostolos Papazacharias, Vincenzo Pierro, Annamaria Porcelli,

Tiziana Quarto, Giuseppe Rizzo, Raffaella Romano, PierluigiGIPPsi/ASL BA

44

Tiziana Quarto, Giuseppe Rizzo, Raffaella Romano, Pierluigi

Selvaggi, Paolo Taurisano

Department of PsychiatryUniversity of Udine

Fabio Sambataro

Angela CarofiglioGiuseppe VerrastroDaria PortnovaCristina Filograno



Conclusions

• Integrating categorical and dimensional approaches improves the reliability of diagnosis

• Common genetic variation is shared between different psychiatric disorders

• The molecular convergence of genetic risk can also be g gidentified with dimensional phenotypes and co‐expression

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17 05 12 Bertolino rischio-geneticopsichiatriamilano2017.it/.../17_05_12_BERTOLINO_rischio-genetico.pdf · La pleiotropia in psichiatria funzionealteratadi un gene che influenza diversitratti