Pleiotropic effects of SCZ-associated genes (Mäki-Marttunen et al. 2017)

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Accession:187615
Python and MATLAB scripts for studying the dual effects of SCZ-related genes on layer 5 pyramidal cell firing and sinoatrial node cell pacemaking properties. The study is based on two L5PC models (Hay et al. 2011, Almog & Korngreen 2014) and SANC models (Kharche et al. 2011, Severi et al. 2012).
Reference:
1 . Mäki-Marttunen T, Lines GT, Edwards AG, Tveito A, Dale AM, Einevoll GT, Andreassen OA (2017) Pleiotropic effects of schizophrenia-associated genetic variants in neuron firing and cardiac pacemaking revealed by computational modeling. Transl Psychiatry 7:5 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Cardiac atrial cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow; Na/Ca exchanger; I_SERCA; Na/K pump; Kir;
Gap Junctions:
Receptor(s):
Gene(s): Nav1.1 SCN1A; Cav3.3 CACNA1I; Cav1.3 CACNA1D; Cav1.2 CACNA1C;
Transmitter(s):
Simulation Environment: NEURON; MATLAB; Python;
Model Concept(s): Schizophrenia;
Implementer(s): Maki-Marttunen, Tuomo [tuomo.maki-marttunen at tut.fi];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow; Na/Ca exchanger; I_SERCA; Na/K pump; Kir;
/
pleiotropy
almog
cells
BK.mod *
ca_h.mod
ca_r.mod
cad.mod *
epsp.mod *
ih.mod *
kfast.mod
kslow.mod
na.mod
SK.mod *
best.params *
calcifcurves.py
calcsteadystate.py
cc_run.hoc *
collectfig1.py
collectfig2.py
fig1_curves.mat
fig2_curves.mat
findDCshortthreshold.py
main.hoc *
model.hoc *
mosinit.hoc *
mutation_stuff.py
myrun.hoc *
mytools.py *
params.hoc *
runme.sh *
scalings.sav
                            
#hoc-code based on implementation https://senselab.med.yale.edu/modeldb/showModel.cshtml?model=151825
#(CC BY 3.0) Tuomo Maki-Marttunen
from neuron import h
import matplotlib
matplotlib.use('Agg')
import numpy
from pylab import *
import mytools
import pickle
import time
import sys

v0 = -62
ca0 = 0.0001
proximalpoint = 400
distalpoint = 620
#distalpoint = 960
BACdt = 5.0
fs = 8
coeffCoeffs = [[0.25,0],[0.125,0],[0.5,0],[0.5,1.0/3],[0.5,2.0/3],[0.5,1.0],[-0.25,0],[-0.125,0],[-0.5,0]]

import mutation_stuff
MT = mutation_stuff.getMT()
defVals = mutation_stuff.getdefvals()
keyList = defVals.keys()
mySuffixes = mutation_stuff.getsuffixes()
mySuffixExceptions = mutation_stuff.getsuffixexceptions()

unpicklefile = open('scalings.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
theseCoeffsAll = unpickledlist[0]
theseMutValsAll = unpickledlist[2]

spTimesAll = []
timesAll = []
VsomasAll = []
CasomasAll = []
VdendsAll = []
CadendsAll = []
ISIs_all = []
InasomasAll = []
IcahvasomasAll = []
IcalvasomasAll = []
IhsomasAll = []
IsksomasAll = []
IbksomasAll = []
InadendsAll = []
IcahvadendsAll = []
IcalvadendsAll = []
IhdendsAll = []
IskdendsAll = []
IbkdendsAll = []

h("""
load_file("myrun.hoc")
objref cvode
cvode = new CVode()
cvode.active(1)
cvode.atol(0.001)

access a_soma
objref st1,syn1, sl
a_soma st1 = new IClamp(0.5)

double siteVec[2]
sl = new List()
sl=locateSites("apic",620)
maxdiam = 0
for(i=0;i<sl.count();i+=1){
  dd1 = sl.o[i].x[1]
  dd = apic[sl.o[i].x[0]].diam(dd1)
  if (dd > maxdiam) {
    j = i
    maxdiam = dd
  }
}
siteVec[0] = sl.o[j].x[0]
siteVec[1] = sl.o[j].x[1]
apic[siteVec[0]] syn1 = new AlphaSynapse(siteVec[1])
//apic[41] syn1 = new AlphaSynapse(0.5)
syn1.onset = 3400
syn1.tau = 3
syn1.gmax = 0.0
syn1.e = 50

objref vsoma, vdend, casoma, cadend, tvec, inasoma, icahvasoma, icalvasoma, ihsoma, isksoma, ibksoma, inadend, icahvadend, icalvadend, ihdend, iskdend, ibkdend, iktsoma, ikpsoma, iktdend, ikpdend
vsoma = new Vector()
vdend = new Vector()
casoma = new Vector()
cadend = new Vector()
inasoma = new Vector()
icahvasoma = new Vector()
icalvasoma = new Vector()
ihsoma = new Vector()
isksoma = new Vector()
ibksoma = new Vector()
inadend = new Vector()
icahvadend = new Vector()
icalvadend = new Vector()
ihdend = new Vector()
iskdend = new Vector()
ibkdend = new Vector()
iktsoma = new Vector()
ikpsoma = new Vector()
iktdend = new Vector()
ikpdend = new Vector()
tvec = new Vector()
a_soma cvode.record(&v(0.5),vsoma,tvec)
a_soma cvode.record(&cai(0.5),casoma,tvec)
a_soma cvode.record(&ina_na(0.5),inasoma,tvec)
a_soma cvode.record(&ica_cah(0.5),icahvasoma,tvec)
a_soma cvode.record(&ica_car(0.5),icalvasoma,tvec)
a_soma cvode.record(&ih_iH(0.5),ihsoma,tvec)
a_soma cvode.record(&ik_sk(0.5),isksoma,tvec)
a_soma cvode.record(&ik_bk(0.5),ibksoma,tvec)
a_soma cvode.record(&ik_iA(0.5),iktsoma,tvec)
a_soma cvode.record(&ik_kslow(0.5),ikpsoma,tvec)
apic[siteVec[0]] cvode.record(&v(siteVec[1]),vdend,tvec)
apic[siteVec[0]] cvode.record(&cai(siteVec[1]),cadend,tvec)
apic[siteVec[0]] cvode.record(&ina_na(siteVec[1]),inadend,tvec)
apic[siteVec[0]] cvode.record(&ica_cah(siteVec[1]),icahvadend,tvec)
apic[siteVec[0]] cvode.record(&ica_car(siteVec[1]),icalvadend,tvec)
apic[siteVec[0]] cvode.record(&ih_iH(siteVec[1]),ihdend,tvec)
apic[siteVec[0]] cvode.record(&ik_sk(siteVec[1]),iskdend,tvec)
apic[siteVec[0]] cvode.record(&ik_bk(siteVec[1]),ibkdend,tvec)
apic[siteVec[0]] cvode.record(&ik_iA(0.5),iktdend,tvec)
apic[siteVec[0]] cvode.record(&ik_kslow(0.5),ikpdend,tvec)

v_init = -62
dt = 0.025
tstop = 1000
""")                                          

counter = -1
for igene in range(0,len(MT)):
  spTimesThisGene = []
  timesThisGene = []
  VsomasThisGene = []
  CasomasThisGene = []
  VdendsThisGene = []
  CadendsThisGene = []
  InasomasThisGene = []
  IcahvasomasThisGene = []
  IcalvasomasThisGene = []
  IhsomasThisGene = []
  IsksomasThisGene = []
  IbksomasThisGene = []
  InadendsThisGene = []
  IcahvadendsThisGene = []
  IcalvadendsThisGene = []
  IhdendsThisGene = []
  IskdendsThisGene = []
  IbkdendsThisGene = []
  for imut in range(0,len(MT[igene])):
    spTimesThisMut = []
    timesThisMut = []
    VsomasThisMut = []
    CasomasThisMut = []
    VdendsThisMut = []
    CadendsThisMut = []
    InasomasThisMut = []
    IcahvasomasThisMut = []
    IcalvasomasThisMut = []
    IhsomasThisMut = []
    IsksomasThisMut = []
    IbksomasThisMut = []
    InadendsThisMut = []
    IcahvadendsThisMut = []
    IcalvadendsThisMut = []
    IhdendsThisMut = []
    IskdendsThisMut = []
    IbkdendsThisMut = []
    IktsomasThisMut = []
    IkpsomasThisMut = []
    IktdendsThisMut = []
    IkpdendsThisMut = []
    nVals = len(MT[igene][imut])*[0]
    thesemutvars = []
    theseCoeffs = theseCoeffsAll[igene][imut]
    for imutvar in range(0,len(MT[igene][imut])):
      thesemutvars.append(MT[igene][imut][imutvar][0])
      if type(MT[igene][imut][imutvar][1]) is int or type(MT[igene][imut][imutvar][1]) is float:
        MT[igene][imut][imutvar][1] = [MT[igene][imut][imutvar][1]]
      nVals[imutvar] = len(MT[igene][imut][imutvar][1])
    cumprodnVals = cumprod(nVals)
    allmutvars = cumprodnVals[len(MT[igene][imut])-1]*[thesemutvars]
    allmutvals = []
    for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
      allmutvals.append([0]*len(thesemutvars))
    for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
      for imutvar in range(0,len(MT[igene][imut])):
        if imutvar==0:
          allmutvals[iallmutval][imutvar] = MT[igene][imut][imutvar][1][iallmutval%nVals[imutvar]]
        else:
          allmutvals[iallmutval][imutvar] = MT[igene][imut][imutvar][1][(iallmutval/cumprodnVals[imutvar-1])%nVals[imutvar]]
      
    for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
      counter = counter + 1                                                                                                                                                               
      if len(sys.argv) > 1 and int(float(sys.argv[1])) != counter:
        continue
      spTimesThisMutVal = []
      timesThisMutVal = []
      VsomasThisMutVal = []
      CasomasThisMutVal = []
      VdendsThisMutVal = []
      CadendsThisMutVal = []
      InasomasThisMutVal = []
      IcahvasomasThisMutVal = []
      IcalvasomasThisMutVal = []
      IhsomasThisMutVal = []
      IsksomasThisMutVal = []
      IbksomasThisMutVal = []
      InadendsThisMutVal = []
      IcahvadendsThisMutVal = []
      IcalvadendsThisMutVal = []
      IhdendsThisMutVal = []
      IskdendsThisMutVal = []
      IbkdendsThisMutVal = []
      IktsomasThisMutVal = []
      IkpsomasThisMutVal = []
      IktdendsThisMutVal = []
      IkpdendsThisMutVal = []
      for iter in [0, 2, 5, 6, 8, -1]:
        if iter >= 0:
          thisCoeff = coeffCoeffs[iter][0]*theseCoeffs[iallmutval] + coeffCoeffs[iter][1]*(1.0 - 0.5*theseCoeffs[iallmutval])
        else:
          thisCoeff = 0
        if iter == -1 and (igene > 0 or imut > 0 or iallmutval > 0):
          continue # do the control only once!
        mutText = ""
        for imutvar in range(0,len(MT[igene][imut])):
          if imutvar > 0 and imutvar%2==0:
            mutText = mutText+"\n"
          mutvars = allmutvars[iallmutval][imutvar]
          mutvals = allmutvals[iallmutval][imutvar]
          if type(mutvars) is str:
            mutvars = [mutvars]
          mutText = mutText + str(mutvars) + ": "
          for kmutvar in range(0,len(mutvars)):
            mutvar = mutvars[kmutvar]
            if (mutvars[kmutvar].find('off') > -1 and mutvars[kmutvar].find('offc') < 0) or mutvars[kmutvar].find('eh') > -1:
              newVal =  defVals[mutvar]+mutvals*thisCoeff
              if mutvals >= 0 and kmutvar==0:
                mutText = mutText + "+" + str(mutvals) +" mV"
              elif kmutvar==0:
                mutText = mutText  + str(mutvals) +" mV"
            else:
              newVal = defVals[mutvar]*(mutvals**thisCoeff)
              if kmutvar==0:
                mutText = mutText + "*" + str(mutvals)
            if kmutvar < len(mutvars)-1:
              mutText = mutText + ", "
            mySuffix = mutvars[kmutvar][mutvars[kmutvar].find('_')+1:len(mutvars[kmutvar])]
            mySuffixInd = next((i for i,x in enumerate(mySuffixes) if x.find(mySuffix) > -1))
            isException = 0
            for jsuffe in range(0,len(mySuffixExceptions[mySuffixInd])):
              if mySuffixExceptions[mySuffixInd][jsuffe][0].find(mutvars[kmutvar]) > -1:
                isException = 1
                exceptionInd = jsuffe

            if not isException:
              print ("""forall if(ismembrane(\""""+mySuffix+"""\")) """+mutvars[kmutvar]+""" = """+str(newVal))
              h("""forall if(ismembrane(\""""+mySuffix+"""\")) """+mutvars[kmutvar]+""" = """+str(newVal))
            else:
              print ("""forall if(ismembrane(\""""+mySuffix+"""\")) """+mySuffixExceptions[isuffix][j][1]+""" = """+str(newVal))
              h("""forall if(ismembrane(\""""+mySuffix+"""\")) """+mySuffixExceptions[isuffix][j][1]+""" = """+str(newVal))

        print mutText
        tstop = 4000.0
        squareAmp = 0.8
        squareDur = 3800.0
        h("""
tstop = """+str(tstop)+"""
v_init = """+str(v0)+"""
cai0_ca_ion = """+str(ca0)+"""
st1.amp = """+str(squareAmp)+"""
st1.del = 200
st1.dur = """+str(squareDur)+"""
syn1.gmax = 0
""")
        h.init()
        h.run()
  
        times=np.array(h.tvec)
        Vsoma=np.array(h.vsoma)
        Vdend=np.array(h.vdend)
        Casoma=np.array(h.casoma)
        Cadend=np.array(h.cadend)
        Inasoma=np.array(h.inasoma)
        Icahvasoma=np.array(h.icahvasoma)
        Icalvasoma=np.array(h.icalvasoma)
        Ihsoma=np.array(h.ihsoma)
        Isksoma=np.array(h.isksoma)
        Ibksoma=np.array(h.ibksoma)
        Inadend=np.array(h.inadend)
        Icahvadend=np.array(h.icahvadend)
        Icalvadend=np.array(h.icalvadend)
        Ihdend=np.array(h.ihdend)
        Iskdend=np.array(h.iskdend)
        Ibkdend=np.array(h.ibkdend)
        Iktsoma=np.array(h.iktsoma)
        Ikpsoma=np.array(h.ikpsoma)
        Iktdend=np.array(h.iktdend)
        Ikpdend=np.array(h.ikpdend)
        spikes = mytools.spike_times(times,Vsoma,-50,-50)
        spTimesThisCoeff = spikes[:]
        nSpikes1 = len(spikes)
  
        if nSpikes1 > 7:
          spts = spikes[len(spikes)-6:len(spikes)]
          istart = next((i for i,x in enumerate(times) if x > spts[0]))
          iend = next((i for i,x in enumerate(times) if x > spts[4]))+7
          nsteps = iend-istart-1
          tdiff = [y-x for x,y in zip(times[istart:iend-1],times[istart+1:iend])]
          cadiff = [y-x for x,y in zip(Casoma[istart:iend-1],Casoma[istart+1:iend])]
          caddiff = [y-x for x,y in zip(Cadend[istart:iend-1],Cadend[istart+1:iend])]
          caderiv1 = [y/x for x,y in zip(tdiff[0:nsteps-1],cadiff[0:nsteps-1])]
          caderiv2 = [y/x for x,y in zip(tdiff[1:nsteps],cadiff[1:nsteps])]
          caderiv = [(x+y)/2.0 for x,y in zip(caderiv1,caderiv2)]
          cadderiv = [y/x for x,y in zip(tdiff,caddiff)]
  
        #Restore default values:
        for imutvar in range(0,len(MT[igene][imut])):
          mutvars = allmutvars[iallmutval][imutvar]
          mutvals = allmutvals[iallmutval][imutvar]
          if type(mutvars) is str:
            mutvars = [mutvars]
          for kmutvar in range(0,len(mutvars)):
            newVal = defVals[mutvars[kmutvar]]
            mySuffix = mutvars[kmutvar][mutvars[kmutvar].find('_')+1:len(mutvars[kmutvar])]
            mySuffixInd = next((i for i,x in enumerate(mySuffixes) if x.find(mySuffix) > -1))
            isException = 0
            for jsuffe in range(0,len(mySuffixExceptions[mySuffixInd])):
              if mySuffixExceptions[mySuffixInd][jsuffe][0].find(mutvars[kmutvar]) > -1:
                isException = 1
                exceptionInd = jsuffe
            if not isException:
              h("""forall if(ismembrane(\""""+mySuffix+"""\")) """+mutvars[kmutvar]+""" = """+str(defVals[mutvars[kmutvar]]))
            else:
              h("""forall if(ismembrane(\""""+mySuffix+"""\")) """+mySuffixExceptions[isuffix][j][1]+""" = """+str(defVals[mutvars[kmutvar]]))

        spTimesThisMutVal.append(spTimesThisCoeff[:])
        timesThisMutVal.append(times[:])
        VsomasThisMutVal.append(Vsoma[:])
        CasomasThisMutVal.append(Casoma[:])
        VdendsThisMutVal.append(Vdend[:])
        CadendsThisMutVal.append(Cadend[:])
        InasomasThisMutVal.append(Inasoma[:])
        IcahvasomasThisMutVal.append(Icahvasoma[:])
        IcalvasomasThisMutVal.append(Icalvasoma[:])
        IhsomasThisMutVal.append(Ihsoma[:])
        IsksomasThisMutVal.append(Isksoma[:])
        IbksomasThisMutVal.append(Ibksoma[:])
        InadendsThisMutVal.append(Inadend[:])
        IcahvadendsThisMutVal.append(Icahvadend[:])
        IcalvadendsThisMutVal.append(Icalvadend[:])
        IhdendsThisMutVal.append(Ihdend[:])
        IskdendsThisMutVal.append(Iskdend[:])
        IbkdendsThisMutVal.append(Ibkdend[:])
        IktsomasThisMutVal.append(Iktsoma[:])
        IkpsomasThisMutVal.append(Ikpsoma[:])
        IktdendsThisMutVal.append(Iktdend[:])
        IkpdendsThisMutVal.append(Ikpdend[:])
        if iter==-1:
          picklelist = [theseCoeffsAll,times,Vsoma,Casoma,Vdend,Cadend,Inasoma, Icahvasoma, Icalvasoma, Ihsoma, Isksoma, Ibksoma,Inadend, Icahvadend, Icalvadend, Ihdend, Iskdend, Ibkdend, Iktsoma, Ikpsoma, Iktdend, Ikpdend, MT]
          file = open('steadystate_control.sav', 'w')
          pickle.dump(picklelist,file)
          file.close()
  
      spTimesThisMut.append(spTimesThisMutVal[:])
      timesThisMut.append(timesThisMutVal[:])
      VsomasThisMut.append(VsomasThisMutVal[:])
      CasomasThisMut.append(CasomasThisMutVal[:])
      VdendsThisMut.append(VdendsThisMutVal[:])
      CadendsThisMut.append(CadendsThisMutVal[:])
      InasomasThisMut.append(InasomasThisMutVal[:])
      IcahvasomasThisMut.append(IcahvasomasThisMutVal[:])
      IcalvasomasThisMut.append(IcalvasomasThisMutVal[:])
      IhsomasThisMut.append(IhsomasThisMutVal[:])
      IsksomasThisMut.append(IsksomasThisMutVal[:])
      IbksomasThisMut.append(IbksomasThisMutVal[:])
      InadendsThisMut.append(InadendsThisMutVal[:])
      IcahvadendsThisMut.append(IcahvadendsThisMutVal[:])
      IcalvadendsThisMut.append(IcalvadendsThisMutVal[:])
      IhdendsThisMut.append(IhdendsThisMutVal[:])
      IskdendsThisMut.append(IskdendsThisMutVal[:])
      IbkdendsThisMut.append(IbkdendsThisMutVal[:])
      IktsomasThisMut.append(IktsomasThisMutVal[:])
      IkpsomasThisMut.append(IkpsomasThisMutVal[:])
      IktdendsThisMut.append(IktdendsThisMutVal[:])
      IkpdendsThisMut.append(IkpdendsThisMutVal[:])
      picklelist = [theseCoeffsAll,timesThisMutVal,VsomasThisMutVal,CasomasThisMutVal,VdendsThisMutVal,CadendsThisMutVal,
                    InasomasThisMutVal, IcahvasomasThisMutVal, IcalvasomasThisMutVal, IhsomasThisMutVal, IsksomasThisMutVal, IbksomasThisMutVal,
                    InadendsThisMutVal, IcahvadendsThisMutVal, IcalvadendsThisMutVal, IhdendsThisMutVal, IskdendsThisMutVal, IbkdendsThisMutVal, IktsomasThisMutVal, IkpsomasThisMutVal, IktdendsThisMutVal, IkpdendsThisMutVal,MT]
      file = open('steadystate_'+str(igene)+'_'+str(imut)+'_'+str(iallmutval)+'.sav', 'w')
      pickle.dump(picklelist,file)
      file.close()
    spTimesThisGene.append(spTimesThisMut[:])
    timesThisGene.append(timesThisMut[:])
    VsomasThisGene.append(VsomasThisMut[:])
    CasomasThisGene.append(CasomasThisMut[:])
    VdendsThisGene.append(VdendsThisMut[:])
    CadendsThisGene.append(CadendsThisMut[:])
  
  spTimesAll.append(spTimesThisGene[:])
  timesAll.append(timesThisGene[:])
  VsomasAll.append(VsomasThisGene[:])
  CasomasAll.append(CasomasThisGene[:])
  VdendsAll.append(VdendsThisGene[:])
  CadendsAll.append(CadendsThisGene[:])
    
#picklelist = [theseCoeffsAll,VsomasAll,CasomasAll,VdendsAll,CadendsAll,MT]
#file = open('steadystate.sav', 'w')
#pickle.dump(picklelist,file)
#file.close()